{"metadata":{"kaggle":{"accelerator":"none","dataSources":[{"datasetId":3920517,"sourceId":6960620,"sourceType":"datasetVersion"}],"dockerImageVersionId":30580,"isGpuEnabled":false,"isInternetEnabled":true,"language":"python","sourceType":"notebook"},"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport time\nimport matplotlib.pyplot as plt\nimport seaborn as sns","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.status.busy":"2023-11-15T05:19:27.920553Z","iopub.execute_input":"2023-11-15T05:19:27.920997Z","iopub.status.idle":"2023-11-15T05:19:28.756218Z","shell.execute_reply.started":"2023-11-15T05:19:27.920960Z","shell.execute_reply":"2023-11-15T05:19:28.755419Z"},"trusted":true},"execution_count":1,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.24.3\n  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n","output_type":"stream"}]},{"cell_type":"code","source":"from sklearn.feature_selection import SelectKBest, chi2\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import StandardScaler\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Conv1D, MaxPooling1D, Flatten, LSTM, GRU\nfrom tensorflow.keras.optimizers import Adam\nfrom sklearn.metrics import classification_report\nfrom sklearn.metrics import confusion_matrix\nfrom tensorflow.keras.utils import plot_model","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:19:28.757948Z","iopub.execute_input":"2023-11-15T05:19:28.758336Z","iopub.status.idle":"2023-11-15T05:19:39.808110Z","shell.execute_reply.started":"2023-11-15T05:19:28.758308Z","shell.execute_reply":"2023-11-15T05:19:39.807293Z"},"trusted":true},"execution_count":2,"outputs":[]},{"cell_type":"code","source":"df = pd.read_csv('/kaggle/input/edgedata/Edge-IIoTset_99.csv', low_memory = False)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:19:39.809242Z","iopub.execute_input":"2023-11-15T05:19:39.809787Z","iopub.status.idle":"2023-11-15T05:20:20.196771Z","shell.execute_reply.started":"2023-11-15T05:19:39.809759Z","shell.execute_reply":"2023-11-15T05:20:20.195779Z"},"trusted":true},"execution_count":3,"outputs":[]},{"cell_type":"code","source":"df.info()","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:20.197917Z","iopub.execute_input":"2023-11-15T05:20:20.198197Z","iopub.status.idle":"2023-11-15T05:20:20.227465Z","shell.execute_reply.started":"2023-11-15T05:20:20.198172Z","shell.execute_reply":"2023-11-15T05:20:20.226540Z"},"trusted":true},"execution_count":4,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 1945449 entries, 0 to 1945448\nData columns (total 99 columns):\n #   Column                     Dtype  \n---  ------                     -----  \n 0   arp.opcode                 float64\n 1   arp.hw.size                float64\n 2   icmp.checksum              float64\n 3   icmp.seq_le                float64\n 4   icmp.transmit_timestamp    float64\n 5   http.content_length        float64\n 6   http.response              float64\n 7   tcp.ack                    float64\n 8   tcp.ack_raw                float64\n 9   tcp.checksum               float64\n 10  tcp.connection.fin         float64\n 11  tcp.connection.rst         float64\n 12  tcp.connection.syn         float64\n 13  tcp.connection.synack      float64\n 14  tcp.dstport                float64\n 15  tcp.flags                  float64\n 16  tcp.flags.ack              float64\n 17  tcp.len                    float64\n 18  tcp.seq                    float64\n 19  udp.port                   float64\n 20  udp.stream                 float64\n 21  udp.time_delta             float64\n 22  dns.qry.name               float64\n 23  dns.qry.qu                 float64\n 24  dns.retransmission         float64\n 25  dns.retransmit_request     float64\n 26  dns.retransmit_request_in  float64\n 27  mqtt.conflag.cleansess     float64\n 28  mqtt.conflags              float64\n 29  mqtt.hdrflags              float64\n 30  mqtt.len                   float64\n 31  mqtt.msgtype               float64\n 32  mqtt.proto_len             float64\n 33  mqtt.topic_len             float64\n 34  mbtcp.len                  float64\n 35  mbtcp.trans_id             float64\n 36  mbtcp.unit_id              float64\n 37  Attack_label               int64  \n 38  Attack_type                object \n 39  http1_encoded              int64  \n 40  http2_encoded              int64  \n 41  http3_encoded              int64  \n 42  dns_encoded                int64  \n 43  mqtt1_encoded              int64  \n 44  mqtt2_encoded              int64  \n 45  mqtt3_encoded              int64  \n 46  http1_0                    float64\n 47  http1_1                    float64\n 48  http1_2                    float64\n 49  http1_3                    float64\n 50  http1_4                    float64\n 51  http1_5                    float64\n 52  http1_6                    float64\n 53  http1_7                    float64\n 54  http1_8                    float64\n 55  http2_0                    float64\n 56  http2_1                    float64\n 57  http2_2                    float64\n 58  http2_3                    float64\n 59  http2_4                    float64\n 60  http3_0                    float64\n 61  http3_1                    float64\n 62  http3_2                    float64\n 63  http3_3                    float64\n 64  http3_4                    float64\n 65  http3_5                    float64\n 66  http3_6                    float64\n 67  http3_7                    float64\n 68  http3_8                    float64\n 69  http3_9                    float64\n 70  http3_10                   float64\n 71  http3_11                   float64\n 72  http3_12                   float64\n 73  dns_0                      float64\n 74  dns_1                      float64\n 75  dns_2                      float64\n 76  dns_3                      float64\n 77  dns_4                      float64\n 78  dns_5                      float64\n 79  dns_6                      float64\n 80  dns_7                      float64\n 81  dns_8                      float64\n 82  dns_9                      float64\n 83  mqtt1_0                    float64\n 84  mqtt1_1                    float64\n 85  mqtt1_2                    float64\n 86  mqtt1_3                    float64\n 87  mqtt1_4                    float64\n 88  mqtt1_5                    float64\n 89  mqtt1_6                    float64\n 90  mqtt1_7                    float64\n 91  mqtt1_8                    float64\n 92  mqtt1_9                    float64\n 93  mqtt1_10                   float64\n 94  mqtt1_11                   float64\n 95  mqtt1_12                   float64\n 96  mqtt2_0                    float64\n 97  mqtt3_0                    float64\n 98  mqtt3_2                    float64\ndtypes: float64(90), int64(8), object(1)\nmemory usage: 1.4+ GB\n","output_type":"stream"}]},{"cell_type":"code","source":"print(df['Attack_type'].value_counts())","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:20.230562Z","iopub.execute_input":"2023-11-15T05:20:20.231180Z","iopub.status.idle":"2023-11-15T05:20:20.443195Z","shell.execute_reply.started":"2023-11-15T05:20:20.231123Z","shell.execute_reply":"2023-11-15T05:20:20.442181Z"},"trusted":true},"execution_count":5,"outputs":[{"name":"stdout","text":"Attack_type\nNormal                   1399624\nDDoS_UDP                  121567\nDDoS_ICMP                  67939\nSQL_injection              50826\nDDoS_TCP                   50062\nVulnerability_scanner      50026\nPassword                   49933\nDDoS_HTTP                  48544\nUploading                  36957\nBackdoor                   24026\nPort_Scanning              19977\nXSS                        15068\nRansomware                  9689\nFingerprinting               853\nMITM                         358\nName: count, dtype: int64\n","output_type":"stream"}]},{"cell_type":"code","source":"# Creating a dictionary of Types\nattacks = {'Normal': 0,'MITM': 1, 'Uploading': 2, 'Ransomware': 3, 'SQL_injection': 4,\n       'DDoS_HTTP': 5, 'DDoS_TCP': 6, 'Password': 7, 'Port_Scanning': 8,\n       'Vulnerability_scanner': 9, 'Backdoor': 10, 'XSS': 11, 'Fingerprinting': 12,\n       'DDoS_UDP': 13, 'DDoS_ICMP': 14}\ndf['Attack_type'] = df['Attack_type'].map(attacks)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:20.444416Z","iopub.execute_input":"2023-11-15T05:20:20.444696Z","iopub.status.idle":"2023-11-15T05:20:20.645673Z","shell.execute_reply.started":"2023-11-15T05:20:20.444670Z","shell.execute_reply":"2023-11-15T05:20:20.644688Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"code","source":"X = df.drop(columns=['Attack_label', 'Attack_type'])\ny = df['Attack_type']","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:20.646913Z","iopub.execute_input":"2023-11-15T05:20:20.647213Z","iopub.status.idle":"2023-11-15T05:20:21.187951Z","shell.execute_reply.started":"2023-11-15T05:20:20.647189Z","shell.execute_reply":"2023-11-15T05:20:21.187096Z"},"trusted":true},"execution_count":7,"outputs":[]},{"cell_type":"code","source":"# Apply the Chi-Squared test\nchi_selector = SelectKBest(chi2, k='all')  # Set k to the desired number of features\nX_kbest = chi_selector.fit_transform(X, y)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:21.189076Z","iopub.execute_input":"2023-11-15T05:20:21.189400Z","iopub.status.idle":"2023-11-15T05:20:24.739561Z","shell.execute_reply.started":"2023-11-15T05:20:21.189373Z","shell.execute_reply":"2023-11-15T05:20:24.738065Z"},"trusted":true},"execution_count":8,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n","output_type":"stream"}]},{"cell_type":"code","source":"# Get the scores for each feature\nchi_scores = chi_selector.scores_\n\n# Combine scores with feature names\nchi_scores = pd.DataFrame({'feature': X.columns, 'score': chi_scores})\n\n# Sort the features by their scores\nchi_scores = chi_scores.sort_values(by='score', ascending=False)\n\nprint(chi_scores)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:24.740999Z","iopub.execute_input":"2023-11-15T05:20:24.742020Z","iopub.status.idle":"2023-11-15T05:20:24.754943Z","shell.execute_reply.started":"2023-11-15T05:20:24.741983Z","shell.execute_reply":"2023-11-15T05:20:24.753939Z"},"trusted":true},"execution_count":9,"outputs":[{"name":"stdout","text":"                    feature         score\n7                   tcp.ack  9.261514e+14\n8               tcp.ack_raw  3.930695e+14\n4   icmp.transmit_timestamp  1.455797e+13\n18                  tcp.seq  7.310825e+12\n20               udp.stream  2.395570e+12\n..                      ...           ...\n89                  mqtt1_8  1.169939e+00\n90                  mqtt1_9  7.799595e-01\n91                 mqtt1_10  7.799595e-01\n85                  mqtt1_4  7.799595e-01\n84                  mqtt1_3  7.799595e-01\n\n[97 rows x 2 columns]\n","output_type":"stream"}]},{"cell_type":"code","source":"selected_features = chi_scores['feature'].tolist()[:93]  # Select top k features","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:24.756301Z","iopub.execute_input":"2023-11-15T05:20:24.756671Z","iopub.status.idle":"2023-11-15T05:20:24.762009Z","shell.execute_reply.started":"2023-11-15T05:20:24.756638Z","shell.execute_reply":"2023-11-15T05:20:24.761039Z"},"trusted":true},"execution_count":10,"outputs":[]},{"cell_type":"code","source":"# Split the data into train (80%) and test (20%) sets\nX_train, X_test, y_train, y_test = train_test_split(X[selected_features], y, test_size=0.2, random_state=42)\n\n# Split the training data further into train (80%) and validation (20%) sets\nX_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=0.125, random_state=42)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:24.763328Z","iopub.execute_input":"2023-11-15T05:20:24.763682Z","iopub.status.idle":"2023-11-15T05:20:28.383310Z","shell.execute_reply.started":"2023-11-15T05:20:24.763648Z","shell.execute_reply":"2023-11-15T05:20:28.382278Z"},"trusted":true},"execution_count":11,"outputs":[]},{"cell_type":"code","source":"print(\"X_train shape:\", X_train.shape)\nprint(\"X_val shape:\", X_val.shape)\nprint(\"X_test shape:\", X_test.shape)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:28.384639Z","iopub.execute_input":"2023-11-15T05:20:28.384953Z","iopub.status.idle":"2023-11-15T05:20:28.389979Z","shell.execute_reply.started":"2023-11-15T05:20:28.384928Z","shell.execute_reply":"2023-11-15T05:20:28.389061Z"},"trusted":true},"execution_count":12,"outputs":[{"name":"stdout","text":"X_train shape: (1361814, 93)\nX_val shape: (194545, 93)\nX_test shape: (389090, 93)\n","output_type":"stream"}]},{"cell_type":"code","source":"scaler = StandardScaler().fit(X_train)\nX_train = scaler.transform(X_train)\nX_val = scaler.transform(X_val)\nX_test = scaler.transform(X_test)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:28.391067Z","iopub.execute_input":"2023-11-15T05:20:28.391378Z","iopub.status.idle":"2023-11-15T05:20:31.114791Z","shell.execute_reply.started":"2023-11-15T05:20:28.391355Z","shell.execute_reply":"2023-11-15T05:20:31.113948Z"},"trusted":true},"execution_count":13,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n","output_type":"stream"}]},{"cell_type":"code","source":"def cnn_lstm_gru_model(input_shape, num_classes):\n    \n    model = Sequential([\n        Conv1D(filters=32, kernel_size=3, activation='relu', input_shape=input_shape),        \n        MaxPooling1D(pool_size=2),\n        \n        Conv1D(filters=64, kernel_size=3, activation='relu'),\n        MaxPooling1D(pool_size=2),\n        \n        LSTM(64, return_sequences=True),\n        GRU(64, return_sequences=False),\n        \n        Flatten(),\n        \n        Dense(128, activation='relu'),\n        Dropout(0.5),\n        Dense(num_classes, activation='softmax')\n    ])\n\n    model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])\n    return model","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:31.118412Z","iopub.execute_input":"2023-11-15T05:20:31.118757Z","iopub.status.idle":"2023-11-15T05:20:31.126460Z","shell.execute_reply.started":"2023-11-15T05:20:31.118716Z","shell.execute_reply":"2023-11-15T05:20:31.125349Z"},"trusted":true},"execution_count":14,"outputs":[]},{"cell_type":"code","source":"input_shape = (X_train.shape[1], 1)\nnum_classes = 15\nmodel = cnn_lstm_gru_model(input_shape, num_classes)\nmodel.summary()\nplot_model(model)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:31.127499Z","iopub.execute_input":"2023-11-15T05:20:31.127818Z","iopub.status.idle":"2023-11-15T05:20:34.487588Z","shell.execute_reply.started":"2023-11-15T05:20:31.127786Z","shell.execute_reply":"2023-11-15T05:20:34.486650Z"},"trusted":true},"execution_count":15,"outputs":[{"name":"stdout","text":"Model: \"sequential\"\n_________________________________________________________________\n Layer (type)                Output Shape              Param #   \n=================================================================\n conv1d (Conv1D)             (None, 91, 32)            128       \n                                                                 \n max_pooling1d (MaxPooling1  (None, 45, 32)            0         \n D)                                                              \n                                                                 \n conv1d_1 (Conv1D)           (None, 43, 64)            6208      \n                                                                 \n max_pooling1d_1 (MaxPoolin  (None, 21, 64)            0         \n g1D)                                                            \n                                                                 \n lstm (LSTM)                 (None, 21, 64)            33024     \n                                                                 \n gru (GRU)                   (None, 64)                24960     \n                                                                 \n flatten (Flatten)           (None, 64)                0         \n                                                                 \n dense (Dense)               (None, 128)               8320      \n                                                                 \n dropout (Dropout)           (None, 128)               0         \n                                                                 \n dense_1 (Dense)             (None, 15)                1935      \n                                                                 \n=================================================================\nTotal params: 74575 (291.31 KB)\nTrainable params: 74575 (291.31 KB)\nNon-trainable params: 0 (0.00 Byte)\n_________________________________________________________________\n","output_type":"stream"},{"execution_count":15,"output_type":"execute_result","data":{"image/png":"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","text/plain":"<IPython.core.display.Image object>"},"metadata":{}}]},{"cell_type":"code","source":"train_start_time = time.time()\n# Train the model\nhistory = model.fit(X_train, y_train, validation_data=(X_val, y_val), epochs=50, batch_size=32)\n# Record the ending time\ntrain_end_time = time.time()\n\n# Record the starting time for testing\ntest_start_time = time.time()\n# Evaluate the model\nloss, accuracy = model.evaluate(X_test, y_test, batch_size=32)\n# Record the ending time for testing\ntest_end_time = time.time()\n\nprint(f'Test Loss: {loss:.4f}')\nprint(f'Test Accuracy: {accuracy:.4f}')\n\n# Calculate and print the training time\ntrain_time = train_end_time - train_start_time\nprint(f\"Training time: {train_time:.2f} seconds\")\n\n# Calculate and print the testing time\ntest_time = test_end_time - test_start_time\nprint(f\"Testing time: {test_time:.2f} seconds\")","metadata":{"execution":{"iopub.status.busy":"2023-11-15T05:20:34.488598Z","iopub.execute_input":"2023-11-15T05:20:34.488896Z","iopub.status.idle":"2023-11-15T09:26:34.613884Z","shell.execute_reply.started":"2023-11-15T05:20:34.488871Z","shell.execute_reply":"2023-11-15T09:26:34.612801Z"},"trusted":true},"execution_count":16,"outputs":[{"name":"stdout","text":"Epoch 1/50\n42557/42557 [==============================] - 310s 7ms/step - loss: 0.1279 - accuracy: 0.9421 - val_loss: 0.0791 - val_accuracy: 0.9625\nEpoch 2/50\n42557/42557 [==============================] - 296s 7ms/step - loss: 0.0794 - accuracy: 0.9627 - val_loss: 0.0718 - val_accuracy: 0.9657\nEpoch 3/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0748 - accuracy: 0.9643 - val_loss: 0.0740 - val_accuracy: 0.9647\nEpoch 4/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0731 - accuracy: 0.9651 - val_loss: 0.0699 - val_accuracy: 0.9667\nEpoch 5/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0718 - accuracy: 0.9655 - val_loss: 0.0757 - val_accuracy: 0.9662\nEpoch 6/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0716 - accuracy: 0.9659 - val_loss: 0.0676 - val_accuracy: 0.9663\nEpoch 7/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0709 - accuracy: 0.9663 - val_loss: 0.0672 - val_accuracy: 0.9668\nEpoch 8/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0703 - accuracy: 0.9667 - val_loss: 0.0722 - val_accuracy: 0.9647\nEpoch 9/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0699 - accuracy: 0.9667 - val_loss: 0.0682 - val_accuracy: 0.9669\nEpoch 10/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0700 - accuracy: 0.9668 - val_loss: 0.0661 - val_accuracy: 0.9674\nEpoch 11/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0700 - accuracy: 0.9669 - val_loss: 0.0652 - val_accuracy: 0.9685\nEpoch 12/50\n42557/42557 [==============================] - 298s 7ms/step - loss: 0.0699 - accuracy: 0.9669 - val_loss: 0.0742 - val_accuracy: 0.9642\nEpoch 13/50\n42557/42557 [==============================] - 296s 7ms/step - loss: 0.0699 - accuracy: 0.9668 - val_loss: 0.0651 - val_accuracy: 0.9680\nEpoch 14/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0700 - accuracy: 0.9670 - val_loss: 0.0644 - val_accuracy: 0.9685\nEpoch 15/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0706 - accuracy: 0.9669 - val_loss: 0.0928 - val_accuracy: 0.9651\nEpoch 16/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0706 - accuracy: 0.9668 - val_loss: 0.0666 - val_accuracy: 0.9670\nEpoch 17/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0700 - accuracy: 0.9670 - val_loss: 0.0666 - val_accuracy: 0.9675\nEpoch 18/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0703 - accuracy: 0.9671 - val_loss: 0.0657 - val_accuracy: 0.9687\nEpoch 19/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0700 - accuracy: 0.9672 - val_loss: 0.0635 - val_accuracy: 0.9686\nEpoch 20/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0703 - accuracy: 0.9673 - val_loss: 0.0761 - val_accuracy: 0.9665\nEpoch 21/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0699 - accuracy: 0.9674 - val_loss: 0.0656 - val_accuracy: 0.9691\nEpoch 22/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0705 - accuracy: 0.9672 - val_loss: 0.0642 - val_accuracy: 0.9688\nEpoch 23/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0711 - accuracy: 0.9673 - val_loss: 0.0657 - val_accuracy: 0.9677\nEpoch 24/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0703 - accuracy: 0.9673 - val_loss: 0.0644 - val_accuracy: 0.9686\nEpoch 25/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0698 - accuracy: 0.9676 - val_loss: 0.0640 - val_accuracy: 0.9687\nEpoch 26/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0733 - accuracy: 0.9671 - val_loss: 0.0646 - val_accuracy: 0.9684\nEpoch 27/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0717 - accuracy: 0.9672 - val_loss: 0.0651 - val_accuracy: 0.9688\nEpoch 28/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0710 - accuracy: 0.9673 - val_loss: 0.0664 - val_accuracy: 0.9676\nEpoch 29/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0713 - accuracy: 0.9671 - val_loss: 0.0661 - val_accuracy: 0.9683\nEpoch 30/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0734 - accuracy: 0.9665 - val_loss: 0.0703 - val_accuracy: 0.9673\nEpoch 31/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0725 - accuracy: 0.9668 - val_loss: 0.0670 - val_accuracy: 0.9678\nEpoch 32/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0721 - accuracy: 0.9667 - val_loss: 0.0665 - val_accuracy: 0.9680\nEpoch 33/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0739 - accuracy: 0.9667 - val_loss: 0.0650 - val_accuracy: 0.9682\nEpoch 34/50\n42557/42557 [==============================] - 297s 7ms/step - loss: 0.0728 - accuracy: 0.9668 - val_loss: 0.0688 - val_accuracy: 0.9665\nEpoch 35/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0740 - accuracy: 0.9666 - val_loss: 0.0717 - val_accuracy: 0.9675\nEpoch 36/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0723 - accuracy: 0.9671 - val_loss: 0.0655 - val_accuracy: 0.9685\nEpoch 37/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0743 - accuracy: 0.9668 - val_loss: 0.0759 - val_accuracy: 0.9673\nEpoch 38/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0728 - accuracy: 0.9667 - val_loss: 0.0653 - val_accuracy: 0.9679\nEpoch 39/50\n42557/42557 [==============================] - 294s 7ms/step - loss: 0.0737 - accuracy: 0.9668 - val_loss: 0.0677 - val_accuracy: 0.9669\nEpoch 40/50\n42557/42557 [==============================] - 302s 7ms/step - loss: 0.0737 - accuracy: 0.9665 - val_loss: 0.0686 - val_accuracy: 0.9678\nEpoch 41/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0778 - accuracy: 0.9660 - val_loss: 0.0651 - val_accuracy: 0.9681\nEpoch 42/50\n42557/42557 [==============================] - 296s 7ms/step - loss: 0.0769 - accuracy: 0.9658 - val_loss: 0.0688 - val_accuracy: 0.9678\nEpoch 43/50\n42557/42557 [==============================] - 295s 7ms/step - loss: 0.0750 - accuracy: 0.9662 - val_loss: 0.0661 - val_accuracy: 0.9684\nEpoch 44/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0767 - accuracy: 0.9661 - val_loss: 0.0667 - val_accuracy: 0.9673\nEpoch 45/50\n42557/42557 [==============================] - 292s 7ms/step - loss: 0.0753 - accuracy: 0.9662 - val_loss: 0.0691 - val_accuracy: 0.9674\nEpoch 46/50\n42557/42557 [==============================] - 293s 7ms/step - loss: 0.0784 - accuracy: 0.9656 - val_loss: 0.0718 - val_accuracy: 0.9653\nEpoch 47/50\n42557/42557 [==============================] - 292s 7ms/step - loss: 0.0777 - accuracy: 0.9656 - val_loss: 0.0751 - val_accuracy: 0.9646\nEpoch 48/50\n42557/42557 [==============================] - 290s 7ms/step - loss: 0.0783 - accuracy: 0.9658 - val_loss: 0.0675 - val_accuracy: 0.9675\nEpoch 49/50\n42557/42557 [==============================] - 288s 7ms/step - loss: 0.0792 - accuracy: 0.9658 - val_loss: 0.0701 - val_accuracy: 0.9674\nEpoch 50/50\n42557/42557 [==============================] - 288s 7ms/step - loss: 0.0773 - accuracy: 0.9658 - val_loss: 0.0642 - val_accuracy: 0.9683\n12160/12160 [==============================] - 40s 3ms/step - loss: 0.0632 - accuracy: 0.9690\nTest Loss: 0.0632\nTest Accuracy: 0.9690\nTraining time: 14719.47 seconds\nTesting time: 40.65 seconds\n","output_type":"stream"}]},{"cell_type":"code","source":"# Plot the training and validation accuracy over the epochs\nplt.plot(history.history['accuracy'])\nplt.plot(history.history['val_accuracy'])\nplt.title('Model accuracy')\nplt.ylabel('Accuracy')\nplt.xlabel('Epoch')\nplt.legend(['Train', 'Validation'], loc='upper left')\nplt.show()\nplt.savefig('acc_plo.jpg')","metadata":{"execution":{"iopub.status.busy":"2023-11-15T09:26:34.615515Z","iopub.execute_input":"2023-11-15T09:26:34.615897Z","iopub.status.idle":"2023-11-15T09:26:34.950524Z","shell.execute_reply.started":"2023-11-15T09:26:34.615867Z","shell.execute_reply":"2023-11-15T09:26:34.949563Z"},"trusted":true},"execution_count":17,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 1 Axes>","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 0 Axes>"},"metadata":{}}]},{"cell_type":"code","source":"# Plot the training and validation loss over the epochs\nplt.plot(history.history['loss'])\nplt.plot(history.history['val_loss'])\nplt.title('Model loss')\nplt.ylabel('Loss')\nplt.xlabel('Epoch')\nplt.legend(['Train', 'Validation'], loc='upper left')\nplt.show()\nplt.savefig('los_plo.jpg')","metadata":{"execution":{"iopub.status.busy":"2023-11-15T09:26:34.951966Z","iopub.execute_input":"2023-11-15T09:26:34.952660Z","iopub.status.idle":"2023-11-15T09:26:35.270478Z","shell.execute_reply.started":"2023-11-15T09:26:34.952622Z","shell.execute_reply":"2023-11-15T09:26:35.269659Z"},"trusted":true},"execution_count":18,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 1 Axes>","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 0 Axes>"},"metadata":{}}]},{"cell_type":"code","source":"y_pred = model.predict(np.expand_dims(X_test, axis=2))","metadata":{"execution":{"iopub.status.busy":"2023-11-15T09:26:35.271512Z","iopub.execute_input":"2023-11-15T09:26:35.271838Z","iopub.status.idle":"2023-11-15T09:27:16.289779Z","shell.execute_reply.started":"2023-11-15T09:26:35.271810Z","shell.execute_reply":"2023-11-15T09:27:16.288783Z"},"trusted":true},"execution_count":19,"outputs":[{"name":"stdout","text":"12160/12160 [==============================] - 33s 3ms/step\n","output_type":"stream"}]},{"cell_type":"code","source":"y_pred_classes = np.argmax(y_pred, axis=1)\n\n# Inverse the 'attacks' dictionary to map back numbers to names\ninverse_attacks = {v: k for k, v in attacks.items()}\n\n# Generate the classification report with attack names instead of numbers\nclass_report = classification_report(y_test, y_pred_classes, target_names=[inverse_attacks[i] for i in range(len(inverse_attacks))])\n\nprint(class_report)","metadata":{"execution":{"iopub.status.busy":"2023-11-15T09:27:16.291259Z","iopub.execute_input":"2023-11-15T09:27:16.291553Z","iopub.status.idle":"2023-11-15T09:27:16.875972Z","shell.execute_reply.started":"2023-11-15T09:27:16.291528Z","shell.execute_reply":"2023-11-15T09:27:16.875057Z"},"trusted":true},"execution_count":20,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n","output_type":"stream"},{"name":"stdout","text":"                       precision    recall  f1-score   support\n\n               Normal       1.00      1.00      1.00    279968\n                 MITM       1.00      1.00      1.00        67\n            Uploading       0.90      0.68      0.78      7426\n           Ransomware       0.90      0.90      0.90      1978\n        SQL_injection       0.62      0.82      0.71     10026\n            DDoS_HTTP       0.95      0.90      0.93      9675\n             DDoS_TCP       0.97      0.93      0.95     10117\n             Password       0.65      0.56      0.60     10102\n        Port_Scanning       0.85      1.00      0.92      3979\nVulnerability_scanner       0.99      0.92      0.96     10023\n             Backdoor       0.98      0.92      0.95      4783\n                  XSS       0.64      0.88      0.74      2963\n       Fingerprinting       1.00      0.27      0.43       161\n             DDoS_UDP       1.00      1.00      1.00     24332\n            DDoS_ICMP       0.99      1.00      1.00     13490\n\n             accuracy                           0.97    389090\n            macro avg       0.90      0.85      0.86    389090\n         weighted avg       0.97      0.97      0.97    389090\n\n","output_type":"stream"}]},{"cell_type":"code","source":"# Compute the confusion matrix\nconf_mat = confusion_matrix(y_test, y_pred_classes)\n\n# Convert the 'attacks' dictionary to a list of class names ordered by the class number\nclass_names_ordered = [attack for attack, number in sorted(attacks.items(), key=lambda item: item[1])]\n\n# Plot the heatmap using seaborn\nplt.figure(figsize=(15, 10))\nsns.heatmap(conf_mat, annot=True, fmt=\"d\", cmap=\"Blues\", xticklabels=class_names_ordered, yticklabels=class_names_ordered)\nplt.xlabel('Predicted Labels')\nplt.ylabel('True Labels')\nplt.title('Confusion Matrix')\nplt.show()\nplt.savefig('con_mat.jpg')","metadata":{"execution":{"iopub.status.busy":"2023-11-15T09:27:16.877076Z","iopub.execute_input":"2023-11-15T09:27:16.877381Z","iopub.status.idle":"2023-11-15T09:27:17.785491Z","shell.execute_reply.started":"2023-11-15T09:27:16.877354Z","shell.execute_reply":"2023-11-15T09:27:17.784551Z"},"trusted":true},"execution_count":21,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x1000 with 2 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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 0 Axes>"},"metadata":{}}]},{"cell_type":"code","source":"# Compute the confusion matrix\nconf_mat = confusion_matrix(y_test, y_pred_classes)\n\n# Normalize the confusion matrix by dividing each value by the sum of its row (i.e., the number of true instances for each label)\nconf_mat_normalized = conf_mat.astype('float') / conf_mat.sum(axis=1)[:, np.newaxis]\n\n# Convert the 'attacks' dictionary to a list of class names ordered by the class number\nclass_names_ordered = [attack for attack, number in sorted(attacks.items(), key=lambda item: item[1])]\n\n# Plot the heatmap using seaborn\nplt.figure(figsize=(15, 10))\nsns.heatmap(conf_mat_normalized, annot=True, fmt=\".2%\", cmap=\"Blues\", xticklabels=class_names_ordered, yticklabels=class_names_ordered)\nplt.xlabel('Predicted Labels')\nplt.ylabel('True Labels')\nplt.title('Normalized Confusion Matrix as Percentages')\nplt.show()\nplt.savefig('con_per.jpg')","metadata":{"execution":{"iopub.status.busy":"2023-11-15T09:27:17.786520Z","iopub.execute_input":"2023-11-15T09:27:17.786805Z","iopub.status.idle":"2023-11-15T09:27:18.676854Z","shell.execute_reply.started":"2023-11-15T09:27:17.786779Z","shell.execute_reply":"2023-11-15T09:27:18.676002Z"},"trusted":true},"execution_count":22,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype):\n/opt/conda/lib/python3.10/site-packages/sklearn/utils/validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x1000 with 2 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3WzZspn054XXz7eLiwtAlHtdxcWgQYO4f/8+mTNnJleuXPz4448cP378rfu872fq9RwQmeV9czRp0oStW7dy5coV1qxZQ5MmTd5Y98qVK3h5eZEkSRIcHR1xd3enTJkywPt93t728/C6JEmSMH78eI4fP07ixIkZP358jPYLDg7mp59+Ik2aNNja2uLm5oa7uzv379836WtsrtWrfvrpJ7Zu3cr27ds5fvw4N27cMD6JNqY/My9YW1tHWQZ+4cIFUqZMSZIkSd7YBz8/PwwGA5kyZYpyHF9f3yjHSZ06dZT7H77PZycmn4MXn9fXP8/Rlfn5+fHgwQOSJk0apf+PHz829r9MmTLUq1ePgQMH4ubmRq1atZg9e3aUezSKiIj823QPOhERkY8kQ4YMNGvWjOnTp9OzZ8831ovuAQbReXXGyevedJ+1N5Ub/rlh/oULF6hQoQJZs2Zl9OjRpEmThgQJErBx40bGjBkT5Z5eMXHx4kWaNm1KpUqVGDJkiMm2F+3Nnz+f5MmTR9n3Qz1VNWvWrACcOHGC2rVrf5A2X/Wu8xob4eHhJu9Lly7NhQsXWLt2LVu2bGHGjBmMGTOGqVOn0rZt27e2FdPP1IfK8eWXX2Jra0vLli0JCQmhYcOG0dYLDw+nUqVK3Lt3jx49epA1a1YSJkzI9evX8fLyeq/P29t+HqKzefNmIHIQ9dq1azF6uu53333H7Nmz6dKlC8WKFSNx4sRYWFjQqFEjk77G5VoB5MqVi4oVK0a77X1/ZmxtbbG0fP/v4CMiIrCwsOD333+P9nPx6gw2iNtn50N+Dl7tf9KkSVm4cGG021/MtrSwsGDFihXs27eP3377jc2bN9O6dWtGjRrFvn37ouQUERH5t2iATkRE5CPq27cvCxYsYPjw4VG2pUuXjoiICPz8/IwztSDygQX3799/4xLBD+m3334jJCSEdevWmcymim7ZXEwEBwdTt25dnJ2dWbx4cZSBAk9PTyDy5v1vGpAAjNmjWzJ49uzZd/ajZMmSuLi4sHjxYnr37v3OB0WkS5cu2nbPnDlj0p8PwcXFhfv375uUhYaGRrsUOkmSJLRq1YpWrVrx+PFjSpcuzYABA9446GOuz5S9vT21a9dmwYIFVK1aFTc3t2jrnThxgnPnzjF37lxatGhhLI/uaacxHWSMiU2bNjFjxgy6d+/OwoULadmyJfv373/ngPCKFSto2bIlo0aNMpY9e/YsyvWD979WMRXTn5l3tbF582bu3bv3xll0np6eGAwG0qdPT+bMmWPd31e96RrG9HPw4vP66hOSX3i9zNPTkz/++IMSJUrEaPC2aNGiFC1alKFDh7Jo0SKaNm3KkiVL4ny9REREYktLXEVERD4iT09PmjVrxrRp07h165bJtmrVqgGRT/x81ejRowGoXr36R+/fi4GrV2e9PHjwgNmzZ8eqva+//ppz586xevVq47LPV1WuXBknJyeGDRsW7f2f7t69C0CKFCnImzcvc+fONVlKuHXr1ij3g4uOg4MDPXr0wNfXlx49ekQ7q2fBggUcOHAAiLwWBw4cYO/evcbtT548Yfr06Xh4eMTovncx5enpyV9//WVSNn369Cgz6AIDA03eOzo6kjFjxrcuxTPnZ6pbt27079+ffv36vbFOdJ83g8HAuHHjotRNmDAhQLSDYe/j/v37xqerDhs2jBkzZnDkyBGGDRv2zn2trKyifHYmTJjwQa5VTMX0Z+Zt6tWrh8FgYODAgVG2vchXt25drKysGDhwYJTMBoMhSsaYeNM1jOnnIGXKlOTMmZN58+bx+PFjY/mff/7JiRMnTOo2bNiQ8PBwBg8eHKUfYWFhxj4EBQVFyZc3b14ALXMVERGz0gw6ERGRj6xPnz7Mnz+fs2fPkiNHDmN5njx5aNmyJdOnT+f+/fuUKVOGAwcOMHfuXGrXrk25cuU+et+++OILEiRIQM2aNenQoQOPHz/m119/JWnSpG98uMWbbNiwgXnz5lGvXj2OHz9ucg8uR0dHateujZOTE1OmTKF58+bkz5+fRo0a4e7uzpUrV9iwYQMlSpRg4sSJAHh7e1O9enVKlixJ69atuXfvHhMmTCBHjhwmf6y/yY8//sipU6cYNWoUO3bsoH79+iRPnpxbt26xZs0aDhw4wJ49ewDo2bMnixcvpmrVqnTu3JkkSZIwd+5cLl68yMqVK2O1ZPBN2rZty9dff029evWoVKkSx44dY/PmzVFmnWXPnp2yZctSoEABkiRJwqFDh1ixYgWdOnV6Y9vm/EzlyZOHPHnyvLVO1qxZ8fT0pFu3bly/fh0nJydWrlwZ7X3LChQoAEDnzp2pXLkyVlZWNGrU6L379f333xMYGMgff/yBlZUVVapUoW3btgwZMoRatWq9tc81atRg/vz5JE6cmOzZs7N3717++OMPXF1dTerF5lrF1Pv8zLxJuXLlaN68OePHj8fPz48qVaoQERHBrl27KFeuHJ06dcLT05MhQ4bQq1cvLl26RO3atUmUKBEXL15k9erVtG/fnm7dur1X3z09PXF2dmbq1KkkSpSIhAkTUqRIkff6HAwbNoxatWpRokQJWrVqRVBQEBMnTiRnzpwmvwfKlClDhw4d8Pb2xsfHhy+++AIbGxv8/PxYvnw548aNo379+sydO5fJkydTp04dPD09efToEb/++itOTk7GAW4RERGz+FefGSsiIvIZmz17tgEwHDx4MMq2li1bGgBDjhw5TMqfP39uGDhwoCF9+vQGGxsbQ5o0aQy9evUyPHv2zKReunTpDNWrV4/S7o4dOwyAYfny5THqS//+/Q2A4e7du8aydevWGXLnzm2ws7MzeHh4GIYPH26YNWuWATBcvHjRWK9MmTKGMmXKGN9fvHjRABhmz55tcszoXunSpYvS78qVKxsSJ05ssLOzM3h6ehq8vLwMhw4dMqm3cuVKQ7Zs2Qy2traG7NmzG1atWmVo2bJllPbeZsWKFYYvvvjCkCRJEoO1tbUhRYoUhq+++sqwc+dOk3oXLlww1K9f3+Ds7Gyws7MzFC5c2LB+/foo/Y7ufL9+LgyG6M+1wWAwhIeHG3r06GFwc3MzODg4GCpXrmw4f/68IV26dIaWLVsa6w0ZMsRQuHBhg7Ozs8He3t6QNWtWw9ChQw2hoaFRjvGquH6mXr/ObwIYOnbs+NY60Z2D06dPGypWrGhwdHQ0uLm5Gdq1a2c4duxYlPMXFhZm+O677wzu7u4GCwsLY84X5/qXX36JcrzXr8PatWsNgGHUqFEm9R4+fGhIly6dIU+ePCbn83VBQUGGVq1aGdzc3AyOjo6GypUrG86cOROraxWdN32e3lT3XT8zLVu2NCRMmDDa/cPCwgy//PKLIWvWrIYECRIY3N3dDVWrVjUcPnzYpN7KlSsNJUuWNCRMmNCQMGFCQ9asWQ0dO3Y0nD171linTJkyUX6XvTj+6z+ba9euNWTPnt1gbW1tcm1i+jkwGAyGJUuWGLJmzWqwtbU15MyZ07Bu3TpDvXr1DFmzZo3Sh+nTpxsKFChgsLe3NyRKlMiQK1cuQ/fu3Q03btwwGAwGw5EjRwyNGzc2pE2b1mBra2tImjSpoUaNGlF+94iIiPzbLAyGONzNWERERERE5F+WN29e3N3do71/oYiIyKdI96ATEREREZH/pOfPnxMWFmZStnPnTo4dO0bZsmXN0ykREZGPQDPoRERERETkP+nSpUtUrFiRZs2akTJlSs6cOcPUqVNJnDgxJ0+ejHI/QBERkU+VHhIhIiIiIiL/SS4uLhQoUIAZM2Zw9+5dEiZMSPXq1fn55581OCciIp8VLXEVEREREZH/pMSJE7N06VKuXbtGSEgI9+7dY/ny5Xh6epq7ayIi8pn666+/qFmzJilTpsTCwoI1a9a8c5+dO3eSP39+bG1tyZgxI3PmzHnv42qATkREREREREREBHjy5Al58uRh0qRJMap/8eJFqlevTrly5fDx8aFLly60bduWzZs3v9dxdQ86ERERERERERGR11hYWLB69Wpq1679xjo9evRgw4YNnDx50ljWqFEj7t+/z6ZNm2J8LM2gExERERERERGRz1ZISAgPHz40eYWEhHyQtvfu3UvFihVNyipXrszevXvfqx09JELiFft8nczdBbMIOjjR3F0QERERERGJl+zi0cjLf/Vv7h613Bg4cKBJWf/+/RkwYECc27516xbJkiUzKUuWLBkPHz4kODgYe3v7GLUTjz4mIiIiIiIiIiIS3/Tq1YsffvjBpMzW1tZMvYmeBuhEREREREREROSzZWtr+9EG5JInT87t27dNym7fvo2Tk1OMZ8+BBuhERERERERERORDsIh/jzooVqwYGzduNCnbunUrxYoVe6924t+ZExERERERERERicbjx4/x8fHBx8cHgIsXL+Lj48OVK1eAyOWyLVq0MNb/+uuv8ff3p3v37pw5c4bJkyezbNky/ve//73XcTVAJyIiIiIiIiIiAhw6dIh8+fKRL18+AH744Qfy5cvHTz/9BMDNmzeNg3UA6dOnZ8OGDWzdupU8efIwatQoZsyYQeXKld/ruBYGg8Hw4WKI/Lf9V58o87HpKa4iIiIiIiLmEa+e4lrge3N3IVrBh8eZuwvvpBl0IiIiIiIiIiIiZqQBOhERERERERERETOKRxMtRURERERERETko4mHT3H9UHTmREREREREREREzEgDdCIiIiIiIiIiImakJa4iIiIiIiIiIhJ3Fhbm7sEnSzPoREREREREREREzEgDdCIiIiIiIiIiImakJa4iIiIiIiIiIhJ3eoprrOnMiYiIiIiIiIiImJEG6ERERERERERERMxIS1xFRERERERERCTu9BTXWNMMOvlk7dy5EwsLC+7fv2/uroiIiIiIiIiIxJoG6AQALy8vLCws+Pnnn03K16xZg8VnOAJeIr8nK8Z2wH/LUIKPTqRm2dxR6vT7pjr+W4Zyb+9oNkzthGdad5PtLk4OzB7aktu7fuHmXyOY0r8JCe0TvPW4tgmsGdOzIdd2DOfu7lEsHtmWpEkSmdRJk9yFVeO/JnDPaC5v82ZYl9pYWb38Uc2TJTV7F/fg7u5RrBjbARcnB+M2KytLdi/sTsEc6WJzWoyWLFpI1UrlKZQvF00bNeDE8eNvrb9l8+/UqlGFQvlyUa92TXb99afJdoPBwKQJ46hQpiSF8+emfRsvLl++ZNweGhpK754/UrxwfmpWq8y+vXtM9p8zawbeQwfHKVNMKLdyv41yK/erlFu5lVu5lVu5Qbk/tviaW+InDdCJkZ2dHcOHDycoKOiDtRkaGvrB2vqQEtrbcuLcdbp4L412e1evinzbuAydhy2hdIuRPAkO5bdJHbFN8HJV+OxhLcnmmYIa30ykXueplMyfkUn9mrz1uCO61aN66Zw07T6TL9qOJYV7YpaMamvcbmlpwarx35DAxppyXqNo99N8mn1ZhJ++qW6sM/mnJvx58BzFGg8ncSJ7urepbNzWpXl59h3z59Cpy7E9NWz6fSMjR3jT4duOLFm+mixZsvJNhzYEBgZGW9/n6BF6/tiVOnXrs3TFGsqVr0CX7zri53fOWGf2zF9ZvHA+ffsPYMHiZdjb2/NN+zaEhIQAsGL5UnxPnWLeoqXUb9CQnt27YjAYALh27SorVyznu+//F+tMyq3cyq3cyq3cyq3cyq3cyq3cn0LuT56F5X/z9Qn4NHop/4qKFSuSPHlyvL2931hn5cqV5MiRA1tbWzw8PBg1apTJdg8PDwYPHkyLFi1wcnKiffv2zJkzB2dnZ9avX0+WLFlwcHCgfv36PH36lLlz5+Lh4YGLiwudO3cmPDzc2Nb8+fMpWLAgiRIlInny5DRp0oQ7d+58kKxbdp9m4OT1rNsR/TcwHZuUY/ivm1m/8wQn/W7Qtt88Urgn5styeQDIkj4ZlUvk4NtBizh48jJ7fPz5YfhyGlTOTwr3xNG26eRoh1ftYvQYvYo/D57jqO9V2vdfQLG8nhTO5QFAxWLZyJYhOa37zOX4uets2X2aQZM30KFhaWysrQDImj45s1bt4fyVOyzbdIgs6ZNFnvtUrrSsXZz+E3+L07mZP3c2des3pHadenhmzEjf/gOxs7NjzaqV0dZfuGAexUuWwqt1WzJ4etKpcxeyZc/OkkULgMhvqRbOn0e7Dt9QrnxFMmfJyhDvEdy9c4ft2/4A4OKFC5QpV56MGTPxVeOmBN27ZxwoHjpoAF1+6Iajo2Occim3ciu3ciu3ciu3ciu3ciu3cv/Xc0v8pQE6MbKysmLYsGFMmDCBa9euRdl++PBhGjZsSKNGjThx4gQDBgygX79+zJkzx6TeyJEjyZMnD0ePHqVfv34APH36lPHjx7NkyRI2bdrEzp07qVOnDhs3bmTjxo3Mnz+fadOmsWLFCmM7z58/Z/DgwRw7dow1a9Zw6dIlvLy8PuYpACIHulK4J2b7/jPGsoePn3Hw5CWK5PYAoEju9AQ9fMqR01eMdbbvP0tEhIFCOaNfXpovW1oS2Fizfd9ZY9m5S7e5cvMeRXKnN7Z78vwN7tx7ZKyzdY8viRPZk90zBQAn/K5ToWhWrKwsKVc4Cyf9bgAwoU8j+oxdw+OnIbHO/jw0FN/TpyharLixzNLSkqJFi3P82NFo9znu40PRosVMyoqXKMlxHx8Arl+7RkDAXYoUfdlmokSJyJU7j7HNzFmzcvTIYZ49e8ae3X/j7u6Oi4sLG9avw9bWlgoVK8U6U0wot3Irt3K/SrlfUm7lVm7lVm7lVu5/L7fEb3qKq5ioU6cOefPmpX///sycOdNk2+jRo6lQoYJx0C1z5sycPn2aX375xWTgrHz58nTt2tX4fteuXTx//pwpU6bg6ekJQP369Zk/fz63b9/G0dGR7NmzU65cOXbs2MFXX30FQOvWrY1tZMiQgfHjx1OoUCEeP34co28tQkJCjFOVXzBEhGNhafXW/ZK7OQGYDJIB3Al8RDLXyG3JXJ24+9r28PAI7j18SrJ/9o/SrqsTIaHPefA4+LV2H5q0eyfwtePeexi5zc0JzsI3AxcyrvdXdGlRgb0+/vwyawuNqxci+Fkoh09dZt2kjmRI7cbyzYcZOHn9W7O+Luh+EOHh4bi6upqUu7q6cvGif7T7BAQE4OrqFqV+QGDAP9vvRpa5RW0zICCyTu069fA7e5Y6X1bDxdmFEaPG8vDBAyZPHM/M2fOZOG4Mm37fSOo0aRk4ZBjJkiV7r1zvotzK/aKPym1KuV/LpNyRZcr9so5yK7dyK7dyK7eY+gzvYf9v0QCdRDF8+HDKly9Pt27dTMp9fX2pVauWSVmJEiUYO3Ys4eHhWFlFDnwVLFgwSpsODg7GwTmAZMmS4eHhYTLQlixZMpMlrIcPH2bAgAEcO3aMoKAgIiIiALhy5QrZs2d/Zw5vb28GDhxoUmaVrBA2KQq/c9//Ml//W3zRdpzxfZLECen3dXUqtRnL6B4N2HfMn0Zdf+XvhT9y8OQlNv510oy9jRkbGxt69+tvUtavTy+aNG3OGd/TbN++jWWr1jJn1gyGDxvC6HETzNTTD0u5X1Ju5VZu5f6UKfdLyq3cyq3cn7L4mlv+G7TEVaIoXbo0lStXplevXrHaP2HChFHKbGxsTN5bWFhEW/ZiEO7JkydUrlwZJycnFi5cyMGDB1m9ejUQ8wdP9OrViwcPHpi8rJMVeOd+twIiZ6y9/nTVpK6JuB0Yue124EPcX9tuZWVJEicHbv+zf5R2Ax9im8CGxI72r7XrZNJuUtfXjpskcnbdm9od3rUuExft4Pqd+5QqmIlVfxzl6bNQNu06RemCmd6Z91Uuzi5YWVlFufFqYGAgbm5u0e7j5uZG4D/fSpnU/+fbKze3yKffBgbEvM0D+/dx4bwfjZo04+DBA5QqVRoHBwe+qFKVQwcPvFemmFBu5X5XH5X7tfrKHVmm3O9sU7mVW7mV+0NRbuV+Vx8/h9wSv2mATqL1888/89tvv7F3715jWbZs2di9e7dJvd27d5M5c2bj7LkP5cyZMwQGBvLzzz9TqlQpsmbN+t4PiLC1tcXJycnk9a7lrQCXrgdy8+4DyhXJYixLlNCOQjk92H/8EgD7j1/ExcmBfNnSGOuULZQZS0sLDp6M/gmqR32vEPo8zKTdTOmSkjZFEvYfv2hsN2fGlLi7vJxZWKFoVh48CsbX/1aUNssWzkzW9MmYsuQvAKwsLY0Pk7CxtsLK8v1+xG0SJCBb9hzs3/fyukdERLB//15y58kX7T658+Zl/759JmX79u4hd968AKRKnRo3N3f273/Z5uPHjzlx/Fi0bYaEhOA9ZBD9BgzCysqKiIhwwsLCAAh7HkZERHiUfeJKuZVbuZX7Vcr9knIrt3Irt3K/pNzK/bFzfxbM/bRWPcVVPje5cuWiadOmjB8/3ljWtWtXtm3bxuDBgzl37hxz585l4sSJUZbCfghp06YlQYIETJgwAX9/f9atW8fgwYM/WPsJ7ROQO3MqcmdOBUQ+GCJ35lSkSe4CwKRFO+jRtgrVy+QiR8aUzBzcnJt3H7BuxzEAzl68zebdp5jUrwkFc6SjWJ4MjOnZkOWbj3Dz7gMAUronxmdVXwrmiHxoxMPHz5izZi/Du9aldMFM5MuWhukDm7HvmD8HTlwC4I+9vvj632LmkJbkypyKisWy0b9jDaYt+4vQ52EmGWwTWDOmR0M6Dl5sfPT33mP+dGhYmlyZU1G7Ql72+kR/f4a3ad6yFatWLGPdmtX4X7jAkEEDCA4OpnadugD06dWdcWNePr23abMW7Nm9i7lzZnHR/wJTJk3g1MmTNGrSDIicGdm0eQt+nTaFndu34XfuLH17dcc9aVLKV6gY5fjTp06mZOkyZMsWuYw5b778bPtjK+fOnmHJ4gXkzZf/vTMpt3Irt3Irt3Irt3Irt3Irt3J/Crkl/tI96OSNBg0axNKlS43v8+fPz7Jly/jpp58YPHgwKVKkYNCgQR/lyaru7u7MmTOH3r17M378ePLnz8/IkSP58ssvP0j7+bOnY8uM743vR3SrB8D8dfto338Bo+b8gYO9LRP7NsY5kT17fC7wZcfJhIS+HCRr1XsuY3o2ZOO074iIMLBmmw9dRyw3bre2tiJL+uTY2yUwlnUfuZKICAOLR7bFNoE1f+zx5Xvvl+c4IsJAve+nMK53I3bO6cqTZyEs/O0Ag6ZsiJKhT4dqbPr7FMfPXTeWdR2xnLnDvNg6owtLfj/I6m0+731uqlStRtC9e0yeOJ6AgLtkyZqNydNm4PrPtO9bN29i+co3EHnz5cd7xEgmjh/LhLGjSZvOg7ETJpEpU+aX56pNO4KDgxk04CcePXpIvvwFmDxtBra2tibH9vM7x5ZNv7N05RpjWaUvqnDowAFatWhKOo/0/DxiFB+Dciu3ciu3ciu3ciu3ciu3ciu3uXNL/GVheDH1RiQesM/XydxdMIuggxPN3QUREREREZF4yS4eTY2yL9HH3F2IVvDuoebuwjtpiauIiIiIiIiIiIgZaYBORERERERERETEjOLRREsREREREREREfloPpEnpv4X6cyJiIiIiIiIiIiYkQboREREREREREREzEhLXEVEREREREREJO4sLMzdg0+WZtCJiIiIiIiIiIiYkQboREREREREREREzEhLXEVEREREREREJO70FNdY05kTERERERERERExIw3QiYiIiIiIiIiImJGWuIqIiIiIiIiISNxpiWus6cyJiIiIiIiIiIiYkQboREREREREREREzEhLXEVEREREREREJO4sLczdg0+WZtCJiIiIiIiIiIiYkQboREREREREREREzEhLXEVEREREREREJO70FNdY05kTERERERERERExIw3QiYiIiIiIiIiImJGWuEq8EnRworm7YBYuhTqZuwtmEV+vt4iIiIiIiFlY6CmusaUZdCIiIiIiIiIiImakAToREREREREREREz0hJXERERERERERGJOz3FNdZ05kRERERERERERMxIA3QiIiIiIiIiIiJmpCWuIiIiIiIiIiISd3qKa6xpBp2IiIiIiIiIiIgZaYBORERERERERETEjLTEVURERERERERE4k5PcY01nTkREREREREREREz0gCdiIiIiIiIiIiIGWmJq4iIiIiIiIiIxJ2e4hprmkEnIiIiIiIiIiJiRhqgExERERERERERMSMtcRURERERERERkbjTU1xjTWdORERERERERETEjDRAJyIiIiIiIiIiYkZa4ioiIiIiIiIiInGnp7jGmmbQiYiIiIiIiIiImJEG6CROvLy8sLCw4Ouvv46yrWPHjlhYWODl5WWsW7t2bQAsLCze+howYACXLl3CwsICKysrrl+/btL2zZs3sba2xsLCgkuXLn20fEsWLaRqpfIUypeLpo0acOL48bfW37L5d2rVqEKhfLmoV7smu/7602S7wWBg0oRxVChTksL5c9O+jReXL7/sf2hoKL17/kjxwvmpWa0y+/buMdl/zqwZeA8dHOs8JfJ7smJsB/y3DCX46ERqls0dpU6/b6rjv2Uo9/aOZsPUTnimdTfZ7uLkwOyhLbm96xdu/jWCKf2bkNA+wVuPa5vAmjE9G3Jtx3Du7h7F4pFtSZokkUmdNMldWDX+awL3jObyNm+GdamNldXLX1F5sqRm7+Ie3N09ihVjO+Di5GDcZmVlye6F3SmYI11sTovR53a9Y0q5lfttlFu5X6Xcyq3cyq3cyg3KLfIxaIBO4ixNmjQsWbKE4OBgY9mzZ89YtGgRadOmjXafmzdvGl9jx47FycnJpKxbt27GuqlSpWLevHkm+8+dO5dUqVJ9nED/2PT7RkaO8KbDtx1Zsnw1WbJk5ZsObQgMDIy2vs/RI/T8sSt16tZn6Yo1lCtfgS7fdcTP75yxzuyZv7J44Xz69h/AgsXLsLe355v2bQgJCQFgxfKl+J46xbxFS6nfoCE9u3fFYDAAcO3aVVauWM533/8v1pkS2tty4tx1ungvjXZ7V6+KfNu4DJ2HLaF0i5E8CQ7lt0kdsU3wcjX87GEtyeaZghrfTKRe56mUzJ+RSf2avPW4I7rVo3rpnDTtPpMv2o4lhXtiloxqa9xuaWnBqvHfkMDGmnJeo2j303yafVmEn76pbqwz+acm/HnwHMUaDydxInu6t6ls3NaleXn2HfPn0KnLsT01n+X1Vm7lVm7lVm7lVm7lVm7lVu5PK/cnz8Lyv/n6BHwavZT/tPz585MmTRpWrVplLFu1ahVp06YlX7580e6TPHly4ytx4sRYWFiYlDk6OhrrtmzZktmzZ5vsP3v2bFq2bPlxAv1j/tzZ1K3fkNp16uGZMSN9+w/Ezs6ONatWRlt/4YJ5FC9ZCq/Wbcng6Umnzl3Ilj07SxYtACK/rVk4fx7tOnxDufIVyZwlK0O8R3D3zh22b/sDgIsXLlCmXHkyZszEV42bEnTvHkFBQQAMHTSALj90Mzk372vL7tMMnLyedTui/+apY5NyDP91M+t3nuCk3w3a9ptHCvfEfFkuDwBZ0iejcokcfDtoEQdPXmaPjz8/DF9Og8r5SeGeONo2nRzt8KpdjB6jV/HnwXMc9b1K+/4LKJbXk8K5PACoWCwb2TIkp3WfuRw/d50tu08zaPIGOjQsjY21FQBZ0ydn1qo9nL9yh2WbDpElfTIAPFK50rJ2cfpP/C3W5wU+z+ut3Mqt3Mqt3Mqt3Mqt3Mqt3J9Wbom/NEAnH0Tr1q1NBtFmzZpFq1atPkjbX375JUFBQfz9998A/P333wQFBVGzZs0P0n50noeG4nv6FEWLFTeWWVpaUrRocY4fOxrtPsd9fChatJhJWfESJTnu4wPA9WvXCAi4S5GiL9tMlCgRuXLnMbaZOWtWjh45zLNnz9iz+2/c3d1xcXFhw/p12NraUqFipQ+c9CWPVK6kcE/M9v1njGUPHz/j4MlLFMntAUCR3OkJeviUI6evGOts33+WiAgDhXJGv7w0X7a0JLCxZvu+s8ayc5duc+XmPYrkTm9s9+T5G9y598hYZ+seXxInsie7ZwoATvhdp0LRrFhZWVKucBZO+t0AYEKfRvQZu4bHT0NinT0+Xm9QbuVWbuU2pdwvKbdyK7dyK7dymyO3xG96iqt8EM2aNaNXr15cvhy5xHD37t0sWbKEnTt3xrltGxsbmjVrxqxZsyhZsiSzZs2iWbNm2NjYxLntNwm6H0R4eDiurq4m5a6urly86B/tPgEBAbi6ukWpHxAY8M/2u5FlblHbDAiIrFO7Tj38zp6lzpfVcHF2YcSosTx88IDJE8czc/Z8Jo4bw6bfN5I6TVoGDhlGsmTJPkhegORuTgAmg2QAdwIfkcw1clsyVyfuvrY9PDyCew+fkuyf/aO06+pESOhzHjwONim/E/jQpN07ga8d997DyG1uTnAWvhm4kHG9v6JLiwrs9fHnl1lbaFy9EMHPQjl86jLrJnUkQ2o3lm8+zMDJ698re3y83qDcyv2yj8ptSrlfy6TckWXK/bKOciu3ciu3cn+U3J8FPcU11jRAJx+Eu7s71atXZ86cORgMBqpXr46bm9u7d4yh1q1bU7x4cYYNG8by5cvZu3cvYWFhb90nJCTEeC+BFwxWttja2n6wfn1oNjY29O7X36SsX59eNGnanDO+p9m+fRvLVq1lzqwZDB82hNHjJpipp/8+X/9bfNF2nPF9ksQJ6fd1dSq1GcvoHg3Yd8yfRl1/5e+FP3Lw5CU2/nXSjL2Nmfh6vZX7JeVWbuVW7k+Zcr+k3Mqt3MotElda4iofTOvWrZkzZw5z586ldevWH7TtXLlykTVrVho3bky2bNnImTPnO/fx9vYmceLEJq9fhnvH6Hguzi5YWVlFuQFpYGDgGwce3dzcCPzn2xmT+v98i+PmFvk01MCAmLd5YP8+Lpz3o1GTZhw8eIBSpUrj4ODAF1WqcujggRhlialbAZEz1l5/umpS10TcDozcdjvwIe6vbbeysiSJkwO3/9k/SruBD7FNYENiR/vX2nUyaTep62vHTRI5u+5N7Q7vWpeJi3Zw/c59ShXMxKo/jvL0WSibdp2idMFMMYlsFB+vNyi3cr+7j8r9Wn3ljixT7ne2qdzKrdzK/aEod/zKLfGbBujkg6lSpQqhoaE8f/6cypUrv3uH99S6dWt27twZ48G/Xr168eDBA5PXjz16xWhfmwQJyJY9B/v37TWWRUREsH//XnLnif7BF7nz5mX/vn0mZfv27iF33rwApEqdGjc3d/bvf9nm48ePOXH8WLRthoSE4D1kEP0GDMLKyoqIiHDjrMGw52FERITHKEtMXboeyM27DyhXJIuxLFFCOwrl9GD/8UsA7D9+ERcnB/JlS2OsU7ZQZiwtLTh4MvonqB71vULo8zCTdjOlS0raFEnYf/yisd2cGVPi7vLyhqsVimblwaNgfP1vRWmzbOHMZE2fjClL/gLAytLS+DAJG2srrCzf71dbfLzeoNzKrdzKbUq5X1Ju5VZu5Vbul5T738v9WTD301r1FFcRsLKywtfXl9OnT2NlZfXB22/Xrh13796lbdu2Mapva2uLk5OTyet9lrc2b9mKVSuWsW7NavwvXGDIoAEEBwdTu05dAPr06s64MaOM9Zs2a8Ge3buYO2cWF/0vMGXSBE6dPEmjJs0AsLCwoGnzFvw6bQo7t2/D79xZ+vbqjnvSpJSvUDHK8adPnUzJ0mXIli07AHnz5WfbH1s5d/YMSxYvIG++/DHO8kJC+wTkzpyK3JlTAZEPhsidORVpkrsAMGnRDnq0rUL1MrnIkTElMwc35+bdB6zbcQyAsxdvs3n3KSb1a0LBHOkolicDY3o2ZPnmI9y8+wCAlO6J8VnVl4I5Ih8a8fDxM+as2cvwrnUpXTAT+bKlYfrAZuw75s+BE5cA+GOvL77+t5g5pCW5MqeiYrFs9O9Yg2nL/iL0uelSZtsE1ozp0ZCOgxcbH3m+95g/HRqWJlfmVNSukJe9PtHfl+JtPsfrrdzKrdzKrdzKrdzKrdzKrdyfVm6Jv3QPOvmgnJyif1DAh2Btbf1B72v3LlWqViPo3j0mTxxPQMBdsmTNxuRpM3D9pw+3bt7E8pWR+Lz58uM9YiQTx49lwtjRpE3nwdgJk8iUKbOxTqs27QgODmbQgJ949Ogh+fIXYPK0GVEGDv38zrFl0+8sXbnGWFbpiyocOnCAVi2aks4jPT+PGMX7yp89HVtmfG98P6JbPQDmr9tH+/4LGDXnDxzsbZnYtzHOiezZ43OBLztOJiT05SBZq95zGdOzIRunfUdEhIE123zoOmK5cbu1tRVZ0ifH3i6Bsaz7yJVERBhYPLIttgms+WOPL997LzVuj4gwUO/7KYzr3Yidc7ry5FkIC387wKApG6Jk6NOhGpv+PsXxc9eNZV1HLGfuMC+2zujCkt8Psnqbz3ufm8/xeiu3ciu3ciu3ciu3ciu3civ3p5Vb4i8Lw4spKCLxwLO3P1fis+VSqJO5u2AWQQcnmrsLIiIiIiISz9nFo6lR9jUnm7sL0Qr+7Vtzd+GdtMRVRERERERERETEjDRAJyIiIiIiIiIiYkbxaKKliIiIiIiIiIh8NBYW5u7BJ0sz6ERERERERERERMxIA3QiIiIiIiIiIiJmpCWuIiIiIiIiIiISdxaaBxZbOnMiIiIiIiIiIiJmpAE6ERERERERERERM9ISVxERERERERERiTs9xTXWNINORERERERERETEjDRAJyIiIiIiIiIiYkZa4ioiIiIiIiIiInGnp7jGms6ciIiIiIiIiIiIGWmATkRERERERERExIy0xFVEREREREREROJOT3GNNc2gExERERERERERMSMN0ImIiIiIiIiIiJiRlriKiIiIiIiIiEicWWiJa6xpBp2IiIiIiIiIiIgZaYBORERERERERETEjLTEVSQeCDo40dxdMIsS3jvM3QWz2N2rnLm7YBZXA4PN3QWzSONqb+4uyL/o4t0n5u6CWaR3T2juLoiIiEgMaIlr7GkGnYiIiIiIiIiIiBlpgE5ERERERERERMSMtMRVRERERERERETiTitcY00z6ERERERERERERMxIA3QiIiIiIiIiIiJmpCWuIiIiIiIiIiISZ3qKa+xpBp2IiIiIiIiIiIgZaYBORERERERERETEjLTEVURERERERERE4kxLXGNPM+hERERERERERETMSAN0IiIiIiIiIiIiZqQlriIiIiIiIiIiEmda4hp7mkEnIiIiIiIiIiJiRhqgExERERERERERMSMtcRURERERERERkTjTEtfY0ww6ERERERERERERM9IAnYiIiIiIiIiIiBlpiauIiIiIiIiIiMSdVrjGmmbQiYiIiIiIiIiImJEG6OK5smXL0qVLl3/9OB4eHowdO/ajH1dERERERERE5L9OA3SfqDcNrM2ZMwdnZ+d/vT/v6+DBg7Rv397c3XinJYsWUrVSeQrly0XTRg04cfz4W+tv2fw7tWpUoVC+XNSrXZNdf/1pst1gMDBpwjgqlClJ4fy5ad/Gi8uXLxm3h4aG0rvnjxQvnJ+a1Sqzb+8ek/3nzJqB99DBHyzfm8SH3O6JEjC4dja2dS3J7p6lWdqhENlSJDJut7exonuVTGz8vhi7e5Zm+deFqZc/ZYzb/yJHUg73K8eohjlNymPS7v8qZWR7t5Js6FyMqjmTmWyrmM2dMV/likXiN4sP1/ukz2EG9uxMizqVqFE6L3t3bX9j3Ykjh1CjdF7WLlvw1jZbN6xKjdJ5o7ymjB5mUs/35DF6f9+Oel8UpUGVEvTo1JqQkGcAPA8NZdSQPjSoUoL2Tb7E59A+k31XLp7D1LE/xzJ19OLD9Y5OfMh96thhhvT6nlb1vqB22fzs27UjSp2rl/0Z2rsLTaqX5qsqxenWoRl3b998Y5t9vm9H7bL5o7wG9+xsrBPd9tpl87N6yVwg8nM+ZmhfGlcrxbfNanPs0H6TY6xeMpfp44Z/oLMQKT5c7+got3K/jXIr96uU+7+d+1NmYWHxn3x9CjRAJ2bh7u6Og4ODubvxVpt+38jIEd50+LYjS5avJkuWrHzToQ2BgYHR1vc5eoSeP3alTt36LF2xhnLlK9Dlu474+Z0z1pk981cWL5xP3/4DWLB4Gfb29nzTvg0hISEArFi+FN9Tp5i3aCn1GzSkZ/euGAwGAK5du8rKFcv57vv/KXccJbKzZpZXfsLCDXRefIwGUw8wZut5Hj17bqzzwxcZKe6ZhH5rfKk/5QCL9l+le9VMlM7s+s72UyS2o0tFT45cvh9l27vaLZXJlSo5k9Jx4THGb7tA3xpZcLa3AcDR1opvy2Vg+O/norQbW/HhegM8exZMBs/MfP2/Xm+tt+ev7Zw9fZwkbu7vbHPM9IXMX/2H8TVk9FQASpSrZKzje/IY/X/sSL5CxRg9bQFjpi+kRt2vsLSI/Od3028rOX/Wl5FT5lKlZj1+GdTLeC5u3bjO5t9W0aJdp9jGjiK+XO/4mvvZs2ek98xMhy49o91+8/pVen/XhlRpPRgydjpjZy6lYYt22CSwfWObPQePZPbKLcbX+NnLsbS0oniZisY6r26fvXIL3/Xoj4WFBcVKVwBg8/pVXDjny/BJc/iiRl1GD+ltPBe3b15n6/rVNGvb8YOdh/hyvZVbuZVbuZX788wt8ZcG6D5jXl5e1K5dm4EDB+Lu7o6TkxNff/01oaGhb9wnKCiIFi1a4OLigoODA1WrVsXPz8+4PTAwkMaNG5MqVSocHBzIlSsXixcvNmnjyZMntGjRAkdHR1KkSMGoUaOiHOf1Ja4WFhbMmDGDOnXq4ODgQKZMmVi3bp3JPuvWrSNTpkzY2dlRrlw55s6di4WFBffv34/dCXqH+XNnU7d+Q2rXqYdnxoz07T8QOzs71qxaGW39hQvmUbxkKbxatyWDpyedOnchW/bsLFkUOQvHYDCwcP482nX4hnLlK5I5S1aGeI/g7p07bN/2BwAXL1ygTLnyZMyYia8aNyXo3j2CgoIAGDpoAF1+6Iajo+NHyRufcnsVT8vthyEM/O0Mp2484sb9Z+zzD+Ja0DNjndypnVh//BaHL9/n5oNnrD56E7/bT8iR0umtbVtawJA62Zn25yWu3w+Osv1d7aZ3S8jhy/fxvfmIzafu8CQknJTOdgB0ruDJisPXufUw5IOdi/hwvQEKFi1J83adKF66/BvrBNy9zbRxP9Ot3zCsrd/9DKXEzklwcXUzvg7s+YsUqdKQK29BY50ZE0dSs15jGjRrTbr0GUmd1oNS5StjkyABEDmbqUiJMqRLn5Hqdb/iwf0gHj6IPBeTRw/F6+suOCT8cOcivlzv+Jq7QJESNG3bkaKlov+cL5wxifxFSuD1dRcyZMpKilRpKFyiDM4uSd7YZiKnxCafc59D+7C1s6NE2ZcD0a9ud3F1Y//ff5IzX0GSp0wNwLXLFylcvAxp03tStU7Dfz7n9wGYOnoYLTp01udcuZVbuZVbuZVb4j0N0H3mtm3bhq+vLzt37mTx4sWsWrWKgQMHvrG+l5cXhw4dYt26dezduxeDwUC1atV4/jxyZtGzZ88oUKAAGzZs4OTJk7Rv357mzZtz4MABYxs//vgjf/75J2vXrmXLli3s3LmTI0eOvLOvAwcOpGHDhhw/fpxq1arRtGlT7t27B8DFixepX78+tWvX5tixY3To0IE+ffrE8ey82fPQUHxPn6JoseLGMktLS4oWLc7xY0ej3ee4jw9FixYzKSteoiTHfXwAuH7tGgEBdylS9GWbiRIlIlfuPMY2M2fNytEjh3n27Bl7dv+Nu7s7Li4ubFi/DltbWypUrMTHFF9yl87sxukbjxheLwdbfyjBwnYFqZMvhWmuaw8pndkN90SRAykF0zmTNok9+/zvvbXtdqU9CHoSylqf6JeMvatdv9uPyZ4iEYnsrMma3BFbG0uuBgWTN01isqZIxJID1+Ia3yi+XO+YiIiIYPSQvtRt1JJ06TO+9/7Pnz9n59aNVKpWyziF/n7QPc6ePoGzSxK6fdOCZrXK0/O7Npw6/vLcpvfMwukTRwkJecaRA3tI4uqOU2IXdmzZQIIECd46oPjefYyn1zu+5n5dREQEh/b9Tco06Rjw47e0rF2BH79pEe0y2Lf5Y+NaSpb/Ajt7+2i3378XyOF9f1OxWm1jWXrPTPie8CEk5BlHD+zFxdUNp8TO/Ll1IzYJbN84oBgb8fV6K7dyK7dyv0q5X/rUcn8OzL2U9VNe4vruKQLySUuQIAGzZs3CwcGBHDlyMGjQIH788UcGDx6MpaXp+Kyfnx/r1q1j9+7dFC8e+Utr4cKFpEmThjVr1tCgQQNSpUpFt27djPt89913bN68mWXLllG4cGEeP37MzJkzWbBgARUqRC5tmTt3LqlTp35nX728vGjcuDEAw4YNY/z48Rw4cIAqVaowbdo0smTJwi+//AJAlixZOHnyJEOHDn1jeyEhIcapyi8YrGyxtX3zUp4Xgu4HER4ejqur6XJGV1dXLl70j3afgIAAXF3dotQPCAz4Z/vdyDK3qG0GBETWqV2nHn5nz1Lny2q4OLswYtRYHj54wOSJ45k5ez4Tx41h0+8bSZ0mLQOHDCNZMtP7k8VVfMmdysWO+gVTsnDfNWbtvkz2FInoVjkTz8MNrD9+C4ARm87Rt3oWNnUpQVh4BBEGGLLhDEevPHhju3nTJKZW3hQ0mX7ojXXe1e5e/3tsPHGb+W0KEBIWwYC1vgSHhtOrWmb6r/WlfoFUfFU4NfefPmfohjP4330a6/MQX653TKxYNBsrKyu+rN8kVvvv27Wdx48fUaHql8ayWzciB1MXzZ5K62//R4aMWdm++Tf6/K89k+asIFWadFSqXotLF87xbfO6ODk702PgCB4/esjCWVPwHjeD+b9O5K/tm0meMjXf9xyAm3vsz0V8vd7xNffrHgTd41nwU1Ytmk3TNt/Sov33HD2wh+E/dWPwmOnkzFvgnW2c8z3JlYvn6dT9pzfW2b75N+wdHCj2yqBbhWq1uOTvx3ct6+OU2Jkf+w/n8aOHLJo9lSFjp7NwxiR2bd9M8lSp+a77AFzdk8Y6Z3y93sqt3C/6qNymlPu1TModWfYfzi3xmwboPnN58uQxuddbsWLFePz4MVevXiVdunQmdX19fbG2tqZIkSLGMldXV7JkyYKvry8A4eHhDBs2jGXLlnH9+nVCQ0MJCQkxHuPChQuEhoaatJEkSRKyZMnyzr7mzp3b+P8TJkyIk5MTd+7cAeDs2bMUKlTIpH7hwoXf2p63t3eU2YJ9+vWn708D3tkXc7GxsaF3v/4mZf369KJJ0+ac8T3N9u3bWLZqLXNmzWD4sCGMHjfBTD39sP7t3JYWFpy+8YhJOyL/cT976zEZkzpSr0BK4wBdo0KpyZk6MV2WHOfmg2fkT+tMjyqZufsolAMXg6K06ZDAikG1sjFk/VnuBz+Psv2FmLQ7/a9LTP/rknGfdqU92O8fRFiEgTal0vHVtIOUyuTKoFrZaTbjzYOB/1X/tc/5+bOnWbdiEeNmLI71t2tbNqyhQJESuLq9HFgwREQAUOXLelT6ZzaRZ+asHDt8gK0b1+LVoTPW1jZ880Nvk7bGev9EzXqN8fc7w96/dzBh1jJWLp7N9HEj6D0k6i0D/uv+a9f73/Jfy/3i/jmFS5TlywbNAMiQKQtnTh1j87oVMRqg+2PjGtJlyEjmbDnfWGfbxnWUrliVBK98GWZtbUOHLqb3fxz/c39q1G3ERb+z7P97J2NnLmX1kjn8OmEEPQeNjE1Es/qvXe9/i3K/pNzKrdzKLRJXWuL6iXJycuLBg6gzee7fv0/ixIk/2nF/+eUXxo0bR48ePdixYwc+Pj5Urlz5rfe1iykbGxuT9xYWFkT88wdubPTq1YsHDx6YvH7s8fYbxL/g4uyClZVVlBuQBgYG4ubmFu0+bm5uBP7z7YxJ/X++xXH756bzgQExb/PA/n1cOO9HoybNOHjwAKVKlcbBwYEvqlTl0MED0e4TF/Eld8CjUC4GPDEpuxjwhOROkfd6s7W2pGP5DIzZcp5dfoGcv/OEZYeus/X0HZoXTRNtm6ld7EnlYs+YRrnY36cM+/uUoXru5JTO7Mb+PmVI7WIXq3Y9XB2oljMZU3ZepGA6Z45eecD9p8/ZevoO2VIkwiGBVazPQ3y53u9y6tgRHgTdo1WDqnxZrgBflivAnVs3mTl5NK0bVn3n/ndu3eDY4f1Url7HpNzFNfJcpPXwNClPky79G5+aefzIQS5fvECNuo047nOIgkVLYmdvT8lyX3DCJ26DsfH1esfX3K9LlNgZKytr0qTLYFKeOl167t659c79nwUH8/f2LSZLV1936vgRrl+9RKXXfhZed+LoQa5e8qdana846XOI/EVLYGdvT4myX3DK53CM8rxJfL3eyq3c7+qjcr9WX7kjy5T7nW2a+9/vT5G5l7J+yktcNUD3icqSJUu093U7cuQImTNnNr4/duwYwcEvb1S/b98+HB0dSZMm6mBAtmzZCAsLY//+/caywMBAzp49S/bs2QHYvXs3tWrVolmzZuTJk4cMGTJw7tzLp+J4enpiY2Nj0kZQUJBJndjmPXTI9I/TgwcPvnUfW1tbnJycTF4xWd4KYJMgAdmy52D/vr3GsoiICPbv30vuPPmi3Sd33rzs37fPpGzf3j3kzpsXgFSpU+Pm5s7+/S/bfPz4MSeOH4u2zZCQELyHDKLfgEFYWVkRERFOWFgYAGHPw4iICI9RlvcRX3Ifu/aAdK6mTxFOm8SBmw8iHxJhbWmBjZUlEf/MOHkhPMKA5Rt+uV8KeErDqQdoMv2Q8fXXuQAOXbpPk+mHuPUgJFbt9q6ehdFbzxP8PBxLSwusLS3+6WPkr+837RcT8eV6v0u5yjWYMHs542cuNb6SuLlTt1FLBo2c8s79t25cS2LnJBQqVsqkPFmKlCRxc+falUsm5devXSZpctN7HgKEhoQwZYw3nbr1izwX4eGE/3MuwsPifi7i6/WOr7lfZ2NjQ8as2bl+9ZJJ+Y2rV3BPFvXz+LrdO7fyPDSUMpWqvbHOHxvW4pk5G+kzZn5jndCQEKaN/Zlvuvb551xEGD/nYWFhhIfrcx4byq3cyq3cr1Lulz613BK/aYDuE/XNN99w7tw5OnfuzPHjxzl79iyjR49m8eLFdO3a1VgvNDSUNm3acPr0aTZu3Ej//v3p1KlTlPvPAWTKlIlatWrRrl07/v77b44dO0azZs1IlSoVtWrVMtbZunUre/bswdfXlw4dOnD79m1jG46OjrRp04Yff/yR7du3c/LkSby8vKI93vvo0KEDZ86coUePHpw7d45ly5YxZ84cgI82Gt68ZStWrVjGujWr8b9wgSGDBhAcHEztOnUB6NOrO+PGvFxu1rRZC/bs3sXcObO46H+BKZMmcOrkSRo1aWbsZ9PmLfh12hR2bt+G37mz9O3VHfekSSlfoWKU40+fOpmSpcuQLVvk4GjefPnZ9sdWzp09w5LFC8ibL79yx9LCfVfJlcqJViXSkdrFnio5k1I3f0qWH7oOwJPQcA5dCuL7ip4USOdMSmc7auZOTvXcydlx9q6xnYG1stGpfORslNDwCC7cfWLyevQsjKehYVy4+4SwCEOM232hTr4UBD0NZZdf5Ld8x64+oJCHCzlTOdG0aGou3H3C45CwOJ2L+HC9AYKfPsXf7wz+fmcAuH3zOv5+Z7hz+yZOiZ3xyJDR5GVtbY1LEldSp/UwttG7S3t+W7nEpN2IiAj++H0dFarUxOq1J79aWFhQr1FLflu5mL93buXGtSvMnzGJa5cv8UU0M4yWzJtOwaIl8cycFYDsufKy56/tXLxwjvWrlpItZ944n4f4cr3ja+7Iz/lZ/P3OAnDn1nX8/c4aZ2zWadSC3Tu2sGX9Km5eu8KGVUs4uOcvqtZqYGxj7LB+zJ8edbnOHxvXUKRkWZwSO0d77KdPHrPnz63vnD23bP6vFChSkgyZIj/nWXPmYd+u7Vy6cI6Nq5eSLVfeWCQ3FV+ut3Irt3Irt3J/nrkl/tI96D5RGTJk4K+//qJPnz5UrFiR0NBQsmbNyvLly6lSpYqxXoUKFciUKROlS5cmJCSExo0bM2DAgDe2O3v2bL7//ntq1KhBaGgopUuXZuPGjcblp3379sXf35/KlSvj4OBA+/btqV27tsly219++YXHjx9Ts2ZNEiVKRNeuXaNdjvs+0qdPz4oVK+jatSvjxo2jWLFi9OnTh2+++SbGs+LeV5Wq1Qi6d4/JE8cTEHCXLFmzMXnaDFz/mf586+ZNLC1eDjzmzZcf7xEjmTh+LBPGjiZtOg/GTphEpkwvZxK0atOO4OBgBg34iUePHpIvfwEmT5sRJYOf3zm2bPqdpSvXGMsqfVGFQwcO0KpFU9J5pOfnER/nXlTxIffpm4/otvwkncpnoF3pdNy4/4xRW/z4/eTLwebeq07TqXwGhtTOjpO9NbcePGPyjousOHzDWCe5k63xvk4xFZN2AZIktKF1yXS0mv1ypuypG49YsO8q4xrlJuhpKP3X+sbyDLwUH643gN/ZU/T+vp3x/YyJke1WqFKT//UeHKM2bt24ysMHpvcf9Dm0j7u3b1Kpeu1o96nVsBmhoaHMmDCSR48ekN4zM4NHTyVFKtNZzJf8z7Nr+xYmzFpmLCtRthInfA7Ro1NrUqVJx48/eceon28TX653fM19/uxp+v2vvfH9rEmjAShXuSbf9xpI0VLl+fqH3qxcOJsZ438hZZp09Bj0C9lzv5w1cPf2LSxeORcA169cwveEDwNGTn7jsXdt34zBAKUqVH5jncv+59m9YytjZrwc6C5epiInfQ7Tu3NbUqVJxw993/zwp5iKL9dbuZVbuZVbuT/P3J+6T2U56X+RheF9/7qUT4aXlxf3799nzZo15u7KRzF06FCmTp3K1atXY7zPs7hNNpJPTAnvHebuglns7lXO3F0wi6uBwe+u9BlK42pv7i7Iv+ji3SfvrvQZSu+e0NxdEBERiTW7eDQ1yrXFYnN3IVqB8xqbuwvvFI8+JvKpmzx5MoUKFcLV1ZXdu3fzyy+/0KlTJ3N3S0REREREREQkTjRAJ58MPz8/hgwZwr1790ibNi1du3alV6+YPZVVRERERERERD4yrXCNNQ3QfcZePEThczFmzBjGjBlj7m6IiIiIiIiIiHxQeoqriIiIiIiIiIiIGWkGnYiIiIiIiIiIxJme4hp7mkEnIiIiIiIiIiJiRhqgExERERERERERMSMtcRURERERERERkTjTEtfY0ww6ERERERERERERM9IAnYiIiIiIiIiIiBlpiauIiIiIiIiIiMSZlrjGnmbQiYiIiIiIiIiImJEG6ERERERERERERMxIS1xFRERERERERCTutMI11jSDTkRERERERERExIw0QCciIiIiIiIiImJGGqATEREREREREZE4s7Cw+E++YmPSpEl4eHhgZ2dHkSJFOHDgwFvrjx07lixZsmBvb0+aNGn43//+x7Nnz2J8PA3QiYiIiIiIiIiI/GPp0qX88MMP9O/fnyNHjpAnTx4qV67MnTt3oq2/aNEievbsSf/+/fH19WXmzJksXbqU3r17x/iYGqATERERERERERH5x+jRo2nXrh2tWrUie/bsTJ06FQcHB2bNmhVt/T179lCiRAmaNGmCh4cHX3zxBY0bN37nrLtXaYBORERERERERETizNxLWd/0CgkJ4eHDhyavkJCQaDOEhoZy+PBhKlasaCyztLSkYsWK7N27N9p9ihcvzuHDh40Dcv7+/mzcuJFq1arF+NxZv8d5FhH5pOzuVc7cXTALl1rjzd0Fswha29ncXZB/0dOQcHN3wSzSuyc0dxdEPrrg0Pj5822fwMrcXRAR+Wx5e3szcOBAk7L+/fszYMCAKHUDAgIIDw8nWbJkJuXJkiXjzJkz0bbfpEkTAgICKFmyJAaDgbCwML7++mstcRUREREREREREQHo1asXDx48MHn16tXrg7W/c+dOhg0bxuTJkzly5AirVq1iw4YNDB48OMZtaAadiIiIiIiIiIjEWWyfmPqx2draYmtrG6O6bm5uWFlZcfv2bZPy27dvkzx58mj36devH82bN6dt27YA5MqViydPntC+fXv69OmDpeW758dpBp2IiIiIiIiIiAiQIEECChQowLZt24xlERERbNu2jWLFikW7z9OnT6MMwllZRd66wGAwxOi4mkEnIiIiIiIiIiLyjx9++IGWLVtSsGBBChcuzNixY3ny5AmtWrUCoEWLFqRKlQpvb28AatasyejRo8mXLx9FihTh/Pnz9OvXj5o1axoH6t5FA3QiIiIiIiIiIhJn/9Ulru/rq6++4u7du/z000/cunWLvHnzsmnTJuODI65cuWIyY65v375YWFjQt29frl+/jru7OzVr1mTo0KExPqaFIaZz7UQ+A8/CzN0DkY9PT3GV+CC+PsXVwVZPeZTPn57iKiKfG7t4NDUqZYdV5u5CtG5Mq2vuLryT7kEnIiIiIiIiIiJiRvFoHFdERERERERERD6az2OFq1loBp2IiIiIiIiIiIgZaYBORERERERERETEjLTEVURERERERERE4uxzeYqrOWgGnYiIiIiIiIiIiBlpgE5ERERERERERMSMtMRVRERERERERETiTEtcY08z6ERERERERERERMxIA3QiIiIiIiIiIiJmpCWuIiIiIiIiIiISZ1riGnuaQSciIiIiIiIiImJGGqATERERERERERExIw3Q/Uu8vLywsLDAwsICGxsb0qdPT/fu3Xn27Jm5uyZvsWTRQqpWKk+hfLlo2qgBJ44ff2v9LZt/p1aNKhTKl4t6tWuy668/TbYbDAYmTRhHhTIlKZw/N+3beHH58iXj9tDQUHr3/JHihfNTs1pl9u3dY7L/nFkz8B46+IPlexPl/nxzO9rb8Eu7Upyd7cW9Vd+yY2QDCmRKalKnX7Mi+M9vw71V37JhaG08UyZ+a5slcqRkxU818Z/XmuANnalZNEOUOkmd7Zn+v4r4z2tN4MpvWDuoVpR2h7ctxfUl7fGb04pGZbOYbKtbMiMrfqoZy9TRiw/XOzrxLfeMqRMplj+7yeurutXfWN//gh+9un1PneoVKZY/O0sWzotS5+jhQ3T7/ltqflGGYvmz8+eOP6LUWThvFtUqlKRahZIsmj/bZNupE8fwalKfsLCwuAd8h/h2vV9Q7viV+4V5s36laL7sjPnF+411vmnbkqL5skd5/fDd18Y6BoOB6ZMnUL1SacoUzUenDq258lruAX17UL5kIRrUqsqBfaa5F8ydycifh3zwfK+Lr9dbuZX7bT6X3J80i//o6xOgAbp/UZUqVbh58yb+/v6MGTOGadOm0b9/f3N36z8vNDTULMfd9PtGRo7wpsO3HVmyfDVZsmTlmw5tCAwMjLa+z9Ej9PyxK3Xq1mfpijWUK1+BLt91xM/vnLHO7Jm/snjhfPr2H8CCxcuwt7fnm/ZtCAkJAWDF8qX4njrFvEVLqd+gIT27d8VgMABw7dpVVq5Yznff/0+5lTvWpnSuQPl8aWk9cgsFOy7kjyNX2DC0DildEwLQtX4Bvq2Zl86TdlD6h6U8eRbGb4NrY2tj9cY2E9rZcOLiXbpM2fnGOsv61iB98sQ0GLyeop0Xc+XOQzYOrYODbeStUKsVTk/Dspmp2XcNfWbvZnLnCrg62QHg5JCAAS2K8b8pOz7YeYgv11u5I2XwzMj6LX8aX9NmLnhj3WfPnpEyVWq+7fwDrm5ub6jzlEyZs9C1Z79ot58/d5Zfp05kkPdIBg77hWmTx3P+n3MWFhbG8GED6d6nP9bWH/dWwPH1eit3/Mr9wulTJ1i9chkZM2V5a72fR41jw9Y/ja9FK9ZiZWVF+UqVjXXmz5nJssUL6NG7PzPmLcHe3p4uHdsbc69ZuYwzp08xY+4iatdrQP/e3Y25b1y/xtpVK/imU5ePlhXi7/VWbuWOD7kl/tIA3b/I1taW5MmTkyZNGmrXrk3FihXZunUrAIGBgTRu3JhUqVLh4OBArly5WLx4scn+ZcuWpXPnznTv3p0kSZKQPHlyBgwYYNxuMBgYMGAAadOmxdbWlpQpU9K5c2fj9qCgIFq0aIGLiwsODg5UrVoVPz8/4/Y5c+bg7OzM+vXryZIlCw4ODtSvX5+nT58yd+5cPDw8cHFxoXPnzoSHhwMwceJEcubMaWxjzZo1WFhYMHXqVGNZxYoV6du3LwAXLlygVq1aJEuWDEdHRwoVKsQff5jOPPDw8GDw4MG0aNECJycn2rdvD8Dff/9NqVKlsLe3J02aNHTu3JknT57E5ZK81fy5s6lbvyG169TDM2NG+vYfiJ2dHWtWrYy2/sIF8yheshRerduSwdOTTp27kC17dpYsivxD0GAwsHD+PNp1+IZy5SuSOUtWhniP4O6dO2zfFnkOLl64QJly5cmYMRNfNW5K0L17BAUFATB00AC6/NANR0fHj5ZZuT/v3HYJrKhdIiN9Zu9m96kb+N98wNBF+7lw8wHtquUCoGOtvAxfeoD1+/w5eSmQtqO2kCJJQr4sFnVW3AtbDl9m4Px9rNvrH+32jCmdKZItBZ0n7eCw3x38rt+n86Qd2CWwpmGZyD+ksqZxYdfx6xw5f4dlf57j4dNQPJI5RZ6L1iX4deMJrt59/MHORXy43sr9kpWVFa5u7saXs4vLG+tmz5GL7/73I5UqV8PGJkG0dYqVKE2Hjt9TtnzFaLdfuuRPxoyZKVi4KIWKFCNjpsxcvhT587Fw3izy5S9I9hy54h7sHeLr9Vbu+JUb4OnTJ/Tv3Z1e/QaSyMnprXUTJ3Y2+X1wYN9ebO3sqPDPAJ3BYGDponm0ateB0uUqkClzFvoP/pmAu3f4a8c2AC5d9KdUmfJk8MxEvYZNCAq6x/1/co8YNoiO33cloa63ciu3cou8Jw3QmcnJkyfZs2cPCRJE/sf/s2fPKFCgABs2bODkyZO0b9+e5s2bc+DAAZP95s6dS8KECdm/fz8jRoxg0KBBxkG+lStXGmfm+fn5sWbNGnLlevkHgJeXF4cOHWLdunXs3bsXg8FAtWrVeP78ubHO06dPGT9+PEuWLGHTpk3s3LmTOnXqsHHjRjZu3Mj8+fOZNm0aK1asAKBMmTKcPn2au3fvAvDnn3/i5ubGzp07AXj+/Dl79+6lbNmyADx+/Jhq1aqxbds2jh49SpUqVahZsyZXrlwxyTly5Ejy5MnD0aNH6devHxcuXKBKlSrUq1eP48ePs3TpUv7++286der04S7KK56HhuJ7+hRFixU3lllaWlK0aHGOHzsa7T7HfXwoWrSYSVnxEiU57uMDwPVr1wgIuEuRoi/bTJQoEbly5zG2mTlrVo4eOcyzZ8/Ys/tv3N3dcXFxYcP6ddja2lKhYqUPnNSUcn/eua2tLLG2suRZqOmyumchYRTPnhKP5E6kSJKQ7T5XjdsePg3l4NnbFMmaItbHfTH77llouLHMYIDQ5+EUzxHZ7vGLAeTPlBRnR1vyZXTH3taaCzcfUDx7CvJ5JmXSumOxPv7r4sv1fl18zQ1w9coVan5Rhno1v6B/nx+5dfPGRz1exoyZuXLlErdu3uDmjetcvXwZT89MXLt6hQ3rVtP+2+8/6vEh/l5v5Y5fuV8Y6T2EEqXKUPiVvsbUb2tWUqlyNeztHYDIGXCBAQEUKvLy3DgmSkSOnLk5cdwHgEyZs3DM5wjPnj1j/96/cftn4H/Txt9IkCDBGwfvP5T4er2VW7njQ+7PwYtbe/3XXp+Cj7u2QkysX78eR0dHwsLCCAkJwdLSkokTJwKQKlUqunXrZqz73XffsXnzZpYtW0bhwoWN5blz5zYui82UKRMTJ05k27ZtVKpUiStXrpA8eXIqVqyIjY0NadOmNe7r5+fHunXr2L17N8WLR/5CWrhwIWnSpGHNmjU0aNAAiBxQmzJlCp6engDUr1+f+fPnc/v2bRwdHcmePTvlypVjx44dfPXVV+TMmZMkSZLw559/Ur9+fXbu3EnXrl0ZN24cAAcOHOD58+fGY+bJk4c8efIY8wwePJjVq1ezbt06k8G28uXL07VrV+P7tm3b0rRpU7p06WLMPn78eMqUKcOUKVOws7OLcr5DQkKMU5VfMFjZYmtr+85rFXQ/iPDwcFxdXU3KXV1duXgx+llCAQEBuLq6RakfEBjwz/bIQUxXt6htBgRE1qldpx5+Z89S58tquDi7MGLUWB4+eMDkieOZOXs+E8eNYdPvG0mdJi0DhwwjWbJk78zyPpT78879OPg5+3xv0qtRYc5eDeL2/ac0LJOZIlmTc+HmA5K7RP5xcifoqcl+d+4/Jdk/22Lj7LUgrtx5yGCv4nSauJ0nz57TuXY+UrsnIrlL5NLaP45cYfGOs/w95iuCQ8NoN3oLT549Z1zHcrQfs5X21XLxTc08BD4MpuOE7fheuRfr/sSX6/26+Jo7R67c9B04lHTp0hMQcJeZ0yfzTZvmLFi+joQJE37QY73gkcGTrzt14ftv2wLw9Xdd8MjgyXdft6bj913Zv/dvZk6bhJW1Nf/r1pt8BQp+8D7E1+ut3PErN8DWTRs5e+Y0sxYse+99T508zoXzfvTu//J+UoH/ZEuSxPTcJHF1JfCfc1OzVl3O+52jcb2aODu7MGTEaB4+fMCvUyYy+dc5TJ00jj82byRV6rT0GTCEpEl1vT8E5VbuF338nHNL/KYBun9RuXLlmDJlCk+ePGHMmDFYW1tTr149AMLDwxk2bBjLli3j+vXrhIaGEhISgoOD6R/FuXPnNnmfIkUK7ty5A0CDBg0YO3YsGTJkoEqVKlSrVo2aNWtibW2Nr68v1tbWFClSxLivq6srWbJkwdfX11jm4OBgHJwDSJYsGR4eHibTeJMlS2Y8poWFBaVLl2bnzp1UrFiR06dP8+233zJixAjOnDnDn3/+SaFChYw5Hj9+zIABA9iwYQM3b94kLCyM4ODgKDPoChY0/WPl2LFjHD9+nIULFxrLDAYDERERXLx4kWzZskU5397e3gwcONCkrE+//vT9aUCUuv8VNjY29O5nel/Cfn160aRpc874nmb79m0sW7WWObNmMHzYEEaPm2Cmnn5Yyv3Sx87deuQWpnWpiP/8NoSFR+Bz/g7L/jpHvoxJ371zLIWFR9Bo6AamfF+Rm0s7EBYewXafq2w6eIlXv8waumg/QxftN77v3bgwO3yu8jwsgh6NClHo20VULezBjK5fUOL7JR+tvx+LPucv/Zu5i5Uobfz/GTNnIUeu3NSpXpFtWzfxZe16H/RYr6pbvxF16zcyvt/w2xocEiYkV+68fFWnOrMWLOXO7dv81KsrK9dvNc6o/9SZ+3qbi3K/9G/mvn3rJqN/8Wb8lBkx+gL2db+tWYlnpszkyJn73ZVfYW1jw4+9TO9BObh/bxo2bsbZM778tWMb85euZsGcmYwePoyfR4177779F5n7epuLcr+k3J9vbvlv0BLXf1HChAnJmDEjefLkYdasWezfv5+ZM2cC8MsvvzBu3Dh69OjBjh078PHxoXLlylEekGBjY2Py3sLCgoiICADSpEnD2bNnmTx5Mvb29nz77beULl3aZAnru0TX/tuOCZH3xtu5cye7du0iX758ODk5GQft/vzzT8qUKWOs261bN1avXs2wYcPYtWsXPj4+5MqVK0rO12c1PH78mA4dOuDj42N8HTt2DD8/P5MBxVf16tWLBw8emLx+7NErRufBxdkFKyurKDcgDQwMxO0NNw13c3MzfrNqUv+fb3Hc3NwjywJi3uaB/fu4cN6PRk2acfDgAUqVKo2DgwNfVKnKoYMHot0nLpT788998dYDvui5Ete6k8nUchalfliGjZUlF2894NY/M+eSvjZbLqmzA7dfm1X3vo6ev0vR7xaTrMFU0jebSa2f1uLqZMfFWw+jrZ85tQuNy2Vl4Px9lM6Vmt0nbxDwMJiVu/zInzEpjvY20e4XE/Hper8qvuZ+XaJETqRN68G1q5c/+rFeuB8UxKzpk+navQ+nTh4nTToP0qT1oEChIoSFhZk8HfJDia/XW7njV+4zvqcIuheIV5P6lCiYixIFc3H08EGWLV5AiYK5jPdMjk5w8FO2bv49ykD9i4fD3Ltnem7uBQZGmZnzwuGD+7l44QL1v2rCkUMHKVayNPb2DlT4ogpHDut6fyjKrdzv6uPnkPtzYO6lrJ/yElcN0JmJpaUlvXv3pm/fvgQHB7N7925q1apFs2bNyJMnDxkyZODcuXPvbug19vb21KxZk/Hjx7Nz50727t3LiRMnyJYtG2FhYezf/3J2SmBgIGfPniV79uxxyvLiPnTLly833muubNmy/PHHH+zevdtYBrB79268vLyoU6cOuXLlInny5Fy6dOmdx8ifPz+nT58mY8aMUV5vmnVga2uLk5OTySum367aJEhAtuw52L9vr7EsIiKC/fv3kjtPvmj3yZ03L/v37TMp27d3D7nz5gUgVerUuLm5s3//yzYfP37MiePHom0zJCQE7yGD6DdgEFZWVkREhBMWFnnvsLDnYUREvPk/OmNLueNP7qchYdwKeoqzoy0V86dj/T5/Lt16yM17TyiXJ42xXiL7BBTKkoz9Z25+kOM+fBpKwMNgPFMmJn/GpKzfF/0ShYmdytNjxi6ePHuOlZUFNlaR/1zZWEf+r5Vl7P+RjY/XG+Jv7tc9ffqEa9euGP8j/d8wbtTPNGragqTJkhMeHkFY2MsvzsLDw3W9PyDljl+5CxYuxsLla5m3ZJXxlS17TipXq8G8JauwsnrzE8i3bd3M89BQqlSraVKeMlVqXN3cOLj/5bl58vgxp04eJ1fuvFHaCQkJ4RfvwfTo29+YO/xF7rAwIsIjouwTV/H1eiu3cseH3BK/aYDOjBo0aICVlRWTJk0iU6ZMbN26lT179uDr60uHDh24ffv2e7U3Z84cZs6cycmTJ/H392fBggXY29uTLl06MmXKRK1atWjXrh1///03x44do1mzZqRKlYpatWrFKUfu3LlxcXFh0aJFJgN0a9asISQkhBIlShjrZsqUiVWrVhlnwDVp0sRkNt6b9OjRgz179tCpUyd8fHzw8/Nj7dq1H+0hEQDNW7Zi1YplrFuzGv8LFxgyaADBwcHUrlMXgD69ujNuzChj/abNWrBn9y7mzpnFRf8LTJk0gVMnT9KoSTMg8puEps1b8Ou0Kezcvg2/c2fp26s77kmTUr5C1JsJT586mZKly5AtW+QAat58+dn2x1bOnT3DksULyJsvv3Ir93urmD8tlQqkI10yJ8rnTcMm77qcuxbEvK2RS90nrfWhR6NCVC+SnhzpXJnZtRI37z0xeULrxqF1+LrGy+VACe1syJ3BjdwZIr959EjuRO4MbqRxf7k0vm7JjJTKlQqP5E7UKJqBDUPq8Ns+f7YdNV3eDtCqcg4CHgSz8cBFAPaevkmZPKkpnCU539XOx+nLgTx4Ehplv/cRX663csP4MSM4cvggN29c5/ixo/Ts2hkrSysqVakOwMB+PZk8YbSx/vPnoZw768u5s76EPX/O3Tu3OXfWl6tXXs64e/r0ibEOwI3r1zl31jfah08c2LeHK1cuUa9hEwCy58jJ5UsX2bv7L9asXIallSVp06X/4Lkhfl5v5Y5fuRMmTIhnxkwmLzt7exIndsYzYyYABvbtyeTxo6Ps+9ualZQuW4HEzs4m5RYWFnzVpAVzZkzjr53bOe93joH9euLmnpTS5SpEaWfWr1MoXrI0WbJG5s6dNx87t23F79xZli9ZRO680Q8kxFV8vN7KrdzxJbfEX7oHnRlZW1vTqVMnRowYwdGjR/H396dy5co4ODjQvn17ateuzYMHD2LcnrOzMz///DM//PAD4eHh5MqVi99++814Y83Zs2fz/fffU6NGDUJDQyldujQbN26MsoT1fVlYWFCqVCk2bNhAyZIlgchBOycnJ7JkyWKyXHX06NG0bt2a4sWL4+bmRo8ePXj4MPolbq/KnTs3f/75J3369KFUqVIYDAY8PT356quv4tT3t6lStRpB9+4xeeJ4AgLukiVrNiZPm2Fc+nDr5k0sLV6OcefNlx/vESOZOH4sE8aOJm06D8ZOmESmTJmNdVq1aUdwcDCDBvzEo0cPyZe/AJOnRb1vip/fObZs+p2lK9cYyyp9UYVDBw7QqkVT0nmk5+cRo/gYlPvzzp3YwZZBXsVJ5ebIvUfPWLv7PP3n7SXsn2/4R604jIOdNRO/K49zQlv2nL7Bl/3WEvL85TeEGVIkxtXJ3vg+f6akbPn55RKhEe0i7/k1/4/TtB8T+cj65C4JGd62FEmdHbgV9ISF287gvSTqsoCkzvb0+KoQ5botN5YdOnebcauPsmpATe4+CKbd6K1xPg/x5XorN9y9fZv+vbrx4MF9nF2SkCdvfn6duxgXlyRA5D2sLC1fZg64e5eWjV9+nhfNn82i+bPJV6AQk3+dC8CZ06fo2N7LWGf86OEAVKtZm34DhxnLnz17xqjhQxj88yjjMZImS07X7n0YMqAPCWwS0G+gd7QPOvoQ4uP1Vu74l/tdbt26icUrP+MAly9d5NjRI4ybMiPafZp7teFZcDA/D+nP40ePyJ03P2MnTY+S+8J5P7Zt2cT8pauMZeUrVubIoYN83aY56dKlZ+CwER8+FPH3eiu3cseH3J+6T2U56X+RhcFgMJi7EyL/lmdh5u6ByMfnUmu8ubtgFkFrO5u7C/IvehoSP5eVONi+ecmeyOciODR+/nzbJ9DPt8jnyi4eTY3y+H69ubsQrUvjapi7C++kJa4iIiIiIiIiIiJmFI/GcUVERERERERE5GPREtfY0ww6ERERERERERERM9IAnYiIiIiIiIiIiBlpiauIiIiIiIiIiMSdVrjGmmbQiYiIiIiIiIiImJEG6ERERERERERERMxIS1xFRERERERERCTO9BTX2NMMOhERERERERERETPSAJ2IiIiIiIiIiIgZaYmriIiIiIiIiIjEmZa4xp5m0ImIiIiIiIiIiJiRBuhERERERERERETMSEtcRUREREREREQkzrTCNfY0g05ERERERERERMSMNEAnIiIiIiIiIiJiRlriKiIiIiIiIiIicaanuMaeZtCJiIiIiIiIiIiYkQboREREREREREREzEhLXEVEREREREREJM60wjX2NEAnIvKZCVrb2dxdMIvUbZeYuwtmcW1GI3N3wSwcbK3M3QWzOH/7sbm7YBYZkzmauwvyL7JPED9/vkVEJH7TElcREREREREREREz0gw6ERERERERERGJMz3FNfY0g05ERERERERERMSMNEAnIiIiIiIiIiJiRlriKiIiIiIiIiIicaYVrrGnGXQiIiIiIiIiIiJmpAE6ERERERERERERM9ISVxERERERERERiTNLS61xjS3NoBMRERERERERETEjDdCJiIiIiIiIiIiYkZa4ioiIiIiIiIhInOkprrGnGXQiIiIiIiIiIiJmpAE6ERERERERERERM9ISVxERERERERERiTMLrXGNNc2gExERERERERERMSMN0ImIiIiIiIiIiJiRlriKiIiIiIiIiEicaYVr7GkGnYiIiIiIiIiIiBlpgO4zN2fOHJydnd9rHy8vL2rXrv1R+vPCpUuXsLCwwMfH56MeR0RERERERETkv04DdB/R3bt3+eabb0ibNi22trYkT56cypUrs3v3bmOdPXv2UK1aNVxcXLCzsyNXrlyMHj2a8PBwk7YsLCxYs2bNe/fhq6++4ty5c++1z7hx45gzZ857H+tNohvwS5MmDTdv3iRnzpwf7Dgfw5JFC6laqTyF8uWiaaMGnDh+/K31t2z+nVo1qlAoXy7q1a7Jrr/+NNluMBiYNGEcFcqUpHD+3LRv48Xly5eM20NDQ+nd80eKF85PzWqV2bd3j8n+c2bNwHvo4A+W702UW7nf5lPLbWlhQc+6uTj8Sw2uTq/PwRE16PplDpM61QukZnm3spybWIeAOY3ImdY5Rm07OdgwvHkBTo2txfVfG7D/52pUzJ3CuL177ZwEzGlk8trrXc2kjcGN8uI3sQ7HRn1J/WLpTLZ9WSgNC7uUil3wN/jcr/ebxIfcp44dYVjvLrRtUJl65Quw/+8dJtuDg5/y67jhtGtYlcZVivN9q/psXrfirW3u+2s73b9uRvOaZWhSrQRd2zVm55YNJnUmDO9PvfIFTF6De3Qybn8eGsq4Yf1oVqM0nVrU4djh/Sb7r1kyjxnjR8Qxvan4cL2jo9zK/TbKrdyvUu7/du5PmYWFxX/y9SnQAN1HVK9ePY4ePcrcuXM5d+4c69ato2zZsgQGBgKwevVqypQpQ+rUqdmxYwdnzpzh+++/Z8iQITRq1AiDwRDnPtjb25M0adL32idx4sTvPevufVlZWZE8eXKsrf+7t0Hc9PtGRo7wpsO3HVmyfDVZsmTlmw5tjNfvdT5Hj9Dzx67UqVufpSvWUK58Bbp81xE/v5cDpLNn/srihfPp238ACxYvw97enm/atyEkJASAFcuX4nvqFPMWLaV+g4b07N7V+Dm4du0qK1cs57vv/6fcyq3c76Fz9Wy0KpeRngsOU7z37wxa5sN3VbPSrmImYx0HW2v2n7vLoGXHYtyujZUlK7uVJa1bQlpN3E3RXhv53+yD3AwKNqnne+0+2b9fY3xVH/qHcVvlvCmpWywdDUbuZOAyH8a0KkQSxwQAJLK3oU+9XHSfdziOZ+Cl+HC943PukGfBeHhmpl3nHtFunzN5ND4H9/B978GMm7OC6vWaMGP8CA7u/jPa+gCOTk7Ua9oa74lzGP3rEspVqcmkEQM5etD0D5Z8hYszY8Vm4+t/fYcZt21dvwp/P1+GTZhNpep1GDu0j/Fc3L55nT82rqZJm28/wBmIFF+ut3Irt3Irt3J/nrkl/tIA3Udy//59du3axfDhwylXrhzp0qWjcOHC9OrViy+//JInT57Qrl07vvzyS6ZPn07evHnx8PCgbdu2zJ07lxUrVrBs2bI49+P1Ja4DBgwgb968zJ8/Hw8PDxInTkyjRo149OiRsc7rM94iIiLw9vYmffr02NvbkydPHlasMP3G/dSpU9SoUQMnJycSJUpEqVKluHDhAgMGDGDu3LmsXbvWOHK9c+fOaJe4/vnnnxQuXBhbW1tSpEhBz549CQsLM24vW7YsnTt3pnv37iRJkoTkyZMzYMCAOJ+jN5k/dzZ16zekdp16eGbMSN/+A7Gzs2PNqpXR1l+4YB7FS5bCq3VbMnh60qlzF7Jlz86SRQuAyG9rFs6fR7sO31CufEUyZ8nKEO8R3L1zh+3bIv9gv3jhAmXKlSdjxkx81bgpQffuERQUBMDQQQPo8kM3HB0dP1pm5VbuzzF34Yyu/H70OluP3eRqwBN+O3SNHadukT+Dq7HO8j2XGLnuFH+evh3jdpuWTo+zoy3Nx+/iwPkArgY8Yc/Zu5y6et+kXliEgTsPnhlf9x6HGrdlTuHEnjN38LkUxKr9V3gUHEY698jsAxrmYfb281y/9zRuJ+AV8eF6x+fc+YuUoEmbbylSqny028+eOk7ZyjXImbcgSZOn5IsadfHwzITfmVNvbDNn3oIUKVWe1OnSkzxVGmrUa0K6DBk5c8LHpJ61jQ0uSdyML8dETsZt165cpGCx0qRN70mV2g15eD+Ihw/uAzB9rDfN232HQ8IPdy7iy/VWbuVWbuVW7s8zt8RfGqD7SBwdHXF0dGTNmjXG0fhXbdmyhcDAQLp16xZlW82aNcmcOTOLFy/+KH27cOECa9asYf369axfv54///yTn3/++Y31vb29mTdvHlOnTuXUqVP873//o1mzZvz5Z+Q37tevX6d06dLY2tqyfft2Dh8+TOvWrQkLC6Nbt240bNiQKlWqcPPmTW7evEnx4sWjHOP69etUq1aNQoUKcezYMaZMmcLMmTMZMmSISb25c+eSMGFC9u/fz4gRIxg0aBBbt279sCeIyOU4vqdPUbTYy75aWlpStGhxjh87Gu0+x318KFq0mElZ8RIlOf7PIOT1a9cICLhLkaIv20yUKBG5cucxtpk5a1aOHjnMs2fP2LP7b9zd3XFxcWHD+nXY2tpSoWKlD5zUlHIr9+eY+8D5QEpnT4ZnskQA5EjjTJFM7mw7cTNO7VbOm4pD5wMY0bwgp8fVZteQKnSpkR3L16bQZ0iWiJNjanFoRA2mdihKqiQOxm0nr94nj0cSEjvYkCedC/YJrPC//YgimdzInc6F6Vv94tTHV8WX6/26+Jo7Olly5Obgnr8IvHsHg8HAiaMHuXHtCnkKFo3R/gaDgeNHDnDj2mWy585vsu2Uz2Fa1a3Idy3qMm3MMB79MwAH4OGZmTMnfQgJeYbPwb24uLrhlNiZv/7YiE2CBG8cUIyN+Hq9lVu5lVu5X6XcL31quT8H5l7K+ikvcf3vri/8xFlbWzNnzhzatWvH1KlTyZ8/P2XKlKFRo0bkzp3beF+4bNmyRbt/1qxZ3/vecTEVERHBnDlzSJQo8o/V5s2bs23bNoYOHRqlbkhICMOGDeOPP/6gWLHIX3YZMmTg77//Ztq0aZQpU4ZJkyaROHFilixZgo2NDQCZM2c2tmFvb09ISAjJkyd/Y58mT55MmjRpmDhxIhYWFmTNmpUbN27Qo0cPfvrpJywtI8eSc+fOTf/+/QHIlCkTEydOZNu2bVSq9GF/UQbdDyI8PBxXV1eTcldXVy5e9I92n4CAAFxd3aLUDwgM+Gf73cgyt6htBgRE1qldpx5+Z89S58tquDi7MGLUWB4+eMDkieOZOXs+E8eNYdPvG0mdJi0DhwwjWbJkHyTvC8qt3C/6+DnlHrfhNInsrdnrXY3wCANWlhYMXXmcFXsvx6ldj6SOpHFLyIq9l2k8+k/SJ3NkRIuC2FhZ8MvayBlJhy8E8t2M/Zy/+ZBkzvb8WCsn63tXoFTf33n8LIwdJ2+xYu9ltvb/gmeh4XT8dR9PQ8L5pUVBvpuxn1blM9KuYiYCH4fww+yDnL3xMNb9jS/X+3XxNXd02n7Xnamjh9D+q6pYWVlhYWnJN137kiNP/rfu9+TxI9o3rMrz56FYWlrRrktPk0G9fIWKU7RkeZKmSMmtG9dYNHMSQ3p2ZtjE2VhZWVG+6pdc9vejS6sGJErsTNeffubxo4csmT2VQWOms2jmZHbv2EyylKnp+GN/XN3f79Ycr4qv11u5lftFH5XblHK/lkm5I8v+w7klftMA3UdUr149qlevzq5du9i3bx+///47I0aMYMaMGcY6b7vPXIIECT5Kvzw8PIyDcwApUqTgzp070dY9f/48T58+jTIAFhoaSr58+QDw8fGhVKlSxsG52PD19aVYsWImI9slSpTg8ePHXLt2jbRp0wKRA3SvelvfQ0JCosxeNFjZYmtrG+t+fmw2Njb07tffpKxfn140adqcM76n2b59G8tWrWXOrBkMHzaE0eMmmKmnH5Zyv6TcHz537cJpqV/Ugw7T9nLm+gNypnVhaJN83LofzNLdl2LdrqUFBDx8xg+zDxJhMHDschApXBzoVDWrcYDu1Vl6p6894LB/ID4ja1KrcFoW/hX5H5cj1pxkxJqTxno/1srBX6dv8zw8gh++zE7pvpv4Ik9KJrcvSoUBW2LdX3PR5/wlc+feuHoJ506fpOeQMbgnS8Hp40f4ddxwXFzdyVOgyBv3s3dIyMhfF/Ms+CknjhxgzuTRJEuRipx5CwJQsnxlY910GTKRLkMmOjarxaljh8mdvzDW1ja0+76nSZsThw+gWt1GXPQ7y4HdOxn16xLWLJ3LzIm/0H3gLx/nBHxE/8Xr/W9Q7peUW7mVW7lF4kpLXD8yOzs7KlWqRL9+/dizZw9eXl7079+fTJkib07u6+sb7X6+vr4ms9A+pNcH0iwsLIiIiIi27uPHjwHYsGEDPj4+xtfp06eN96Gzt7f/KP2Mzvv03dvbm8SJE5u8fhnuHaPjuDi7YGVlFeUGpIGBgbi5uUW7j5ubG4H/fDtjUv+fb3Hc3NwjywJi3uaB/fu4cN6PRk2acfDgAUqVKo2DgwNfVKnKoYMHYpTlfSi3cr+rj59i7gEN8zJu42lW77+C77UHLN9ziambz9KlRvY4tXv7/jMu3HpExCtftJy7ETlTzsYq+n9eHz59zoVbj0ifNPp7l2RMkYgGxTzwXnWCElmTsvfsXQIfhbD2wBXyeCTB0S7236vFl+v9uvia+3UhIc9YNHMSXt/+j0LFS+PhmYlqdb6iRLlKrFs2/637WlpakiJVGtJnzMKXDZtTrEwFVi2a/cb6yVOmximxM7euX412+4mjB7l6yZ+qtb/i5LHD5C9SAjt7e4qXqcSpY3F7KEp8vd7Krdzv6qNyv1ZfuSPLlPudbZr73+9PkYXFf/P1KdAA3b8se/bsPHnyhMqVK5MkSRJGjRoVpc66devw8/PDy8vr3+/ga7Jnz46trS1XrlwhY8aMJq80adIAkbPadu3axfPnz6NtI0GCBISHh7/1ONmyZWPv3r0mMwp3795NokSJSJ06daz63qtXLx48eGDy+rFHrxjta5MgAdmy52D/vr3GsoiICPbv30vuPPmi3Sd33rzs37fPpGzf3j3kzpsXgFSpU+Pm5s7+/S/bfPz4MSeOH4u2zZCQELyHDKLfgEFYWVkRERFufGhG2PMwIiLefk5jQ7mV+3PMbW9rheG1cfzwCAOWcfyHer9fAOmTJTL5B98zeSJuBQXzPDz6Lw4S2lrjkdSR2/eDo90+umUh+i05ypOQMKwsLYwDfdbWkf9rGYdOx5fr/br4mvt14WFhhIWFYWFh+p9+lpZWGN7wRdebGCIMhL3h33yAwLu3efTwAS5Jov6xExoawozxw+nwQ2/juQj/51yEh4cR8Y7/XniX+Hq9lVu5lVu5X6XcL31quSV+0wDdRxIYGEj58uVZsGABx48f5+LFiyxfvpwRI0ZQq1YtEiZMyLRp01i7di3t27fn+PHjXLp0iZkzZ+Ll5UW7du2oVq2aSZsXL140mcXm4+PDkydPPmqORIkS0a1bN/73v/8xd+5cLly4wJEjR5gwYQJz584FoFOnTjx8+JBGjRpx6NAh/Pz8mD9/PmfPngUil9QeP36cs2fPEhAQEO1A3rfffsvVq1f57rvvOHPmDGvXrqV///788MMPxvvPvS9bW1ucnJxMXu+zvLV5y1asWrGMdWtW43/hAkMGDSA4OJjadeoC0KdXd8aNeTnA2rRZC/bs3sXcObO46H+BKZMmcOrkSRo1aQZEzvZr2rwFv06bws7t2/A7d5a+vbrjnjQp5StUjHL86VMnU7J0GbJli5zlkzdffrb9sZVzZ8+wZPEC8v6fvbuOyyJbwDj+IyQUVxBULCzs7u527Y611lhz7e5ede1cu1tXXXvXWLu7ELtQQbBpuH+wvvoKBooX8X2+9zOfKzNnzpxnDqtw3nNmcn74mUGfS7mV+3vLvf30fbpUyUTZ7IlJ7hSHSrmS0rZ8ejafuGcoYx/Hiiwu9qRPEvbmSVfnuGRxsSdhPBtDmWmt8tO/9ptl9vN3X8UhjhUjG+UiTaK4lM2emM6VMzF315sXOwypl4NC6ROQ3CkOeV0dWdixCMEhoaw7cjtcOxsXT43Xc3+2n74PhA0AFs2YkNxpHGlbLj2X7z3l2av3D4p8ClPob1PO7ev7ihtX3bhxNezf30ce97lx1Q3Phx7EjmNH5uy5WfTHJM6fPs5Dj3vs2raRf3dsJl+RkoY6Jo8ayJLZb5brrFs2jzPHD/Pg/l3u3rrBxlWL+ffvzRQrU9FwzYUzJ3Ll4jkePbjP2ZNH+a1/V5yTJidHXuMHdQOsXjyHXPkKkzptBgAyZMnO4X27uHnNna3rV5IhS/Yvvg+m0t/KrdzKrdzK/X3mFtOlZ9B9JXZ2duTPn58JEyZw7do1AgMDSZ48Oa1ataJv374A1K5dm927dzNixAiKFi3Ks2dhD/8ePXo0PXv2DFdn165dw+3bt28fRYoU+apZhg0bRoIECRg1ahTXr1/H3t6eXLlyGXI4Ojqya9cuevToQfHixbGwsCBHjhwULlwYgFatWrFnzx7y5MnDixcv2L17NylTpjS6RtKkSdmyZQs9evQge/bsxI8fnxYtWtC/f/+vmu1DKlSshI+3N9OnTsbLy5P0GTIy/Y85OP43/fmBhwfmb81EyJEzF6PG/M7UyROZMnE8LilSMnHKNNKmfbNUuXmLVvj6+jJ08ECeP39Gzly5mf7HnHADh+7uV9ixbSsr16437CtbrgLHjx6leZNGpEiZit/GhJ99qdzKrdzh9Vlygt41szKmcR6cfrDmwRM/Fu65xu//PScOoELOpExt+eYZXHPahf399fbz4ZI5xiHkrceG3vd+RZ3f9zC8YU7+HV4BDx9fZv19hcmb3zy6IEl8W2a1KYSDnRWPn/tzxN2TCsP+4fFz4+djJvjBmi5VMlNp+Ju3Up+64c30bW4s71IMr2d+tJ995IvvhSn0tynnvuZ2kUFdfzF8vWDGeABKlK9Mx15D6DJgJEtnT2XSiP68eP4Mp0TONGjRjvJVaxvO8Xr0ALO3Zmr6+foxa9JveHs+wsramqTJU9Kp73AKlywHhC1/vXXdnT07NvHqxfOw59nlKUCD5m2J9c6zdG/fuMrBPX8zbtabt9QXLFaGC6dPMKBzC5IkS0nn/uFfWBVZptLfyq3cyq3cyv195o7pYsobU79FZqEfekuB/F/5+flRrVo17ty5w7///kuCBAmipR0NGjTAwsKCJUuWRMv1vya/oOhugYh8LclarojuJkSLu3PqR3cT5P/o6sMX0d2EaOGaKOLnNoqIiMQEX/AY4Rgn55Bd0d2ECJ0aVCq6m/BRWuL6DbGxsWHDhg00adKEvXv3/t+vHxQUxMWLFzl06BCZM2f+v19fRERERERERMQUaYDuG2NjY0Pv3r2pVavWJ5WvWLEidnZ2EW4jR46M1LXPnz9Pnjx5yJw5M23atPmc5ouIiIiIiIiIiYrut7XG5Le4mtBEy+/TnDlz8PWN+G2A8ePHj1RdOXLk4NWrV1HRLBERERERERER+UQaoIvhkiZNGt1NEBERERERERGRL6ABOhERERERERER+WJ6i+vn0zPoREREREREREREopEG6ERERERERERERKKRlriKiIiIiIiIiMgX0wrXz6cZdCIiIiIiIiIiItFIA3QiIiIiIiIiIiLRSEtcRURERERERETki+ktrp9PM+hERERERERERESikQboREREREREREREopGWuIqIiIiIiIiIyBfTCtfPpxl0IiIiIiIiIiIi0UgDdCIiIiIiIiIiItFIS1xFREREREREROSL6S2un08z6ERERERERERERKKRBuhERERERERERESikZa4ioiIiIiIiIjIF9MK18+nAToREfku3J1TP7qbEC0cqk6K7iZEC5+NnaK7CdHCNZFddDdB/o9CQkOjuwnRwtxEf7vzeRkQ3U2IFg5xrKK7CSIi3wQtcRUREREREREREYlGmkEnIiIiIiIiIiJfTG9x/XyaQSciIiIiIiIiIhKNNEAnIiIiIiIiIiISjbTEVUREREREREREvphWuH4+zaATERERERERERGJRhqgExERERERERERiUZa4ioiIiIiIiIiIl9Mb3H9fJpBJyIiIiIiIiIiEo00QCciIiIiIiIiIhKNtMRVRERERERERES+mFa4fj7NoBMREREREREREYlGGqATERERERERERGJRlriKiIiIiIiIiIiX0xvcf18mkEnIiIiIiIiIiISjTRAJyIiIiIiIiIiEo20xFVERERERERERL6Ylrh+Ps2gExERERERERERiUYaoBMREREREREREYlGWuIqIiIiIiIiIiJfTCtcP59m0H1DmjVrhpmZGWZmZsSKFYtEiRJRtmxZ5s2bR0hIiKFcypQpDeVsbW1JmTIldevWZdeuXZG+pqenJ23btsXFxQVra2ucnZ0pX748Bw4c+KTzU6ZMycSJE8PtHzx4MDly5AjX3oi2t3NHtKVMmRKAEiVKGPbZ2NiQKVMmpk+fHunMkbFi2VIqli1F3pxZaVS/DufOnv1g+R3bt1KtcgXy5sxKrepV2Lf3X6PjoaGhTJsyidLFi5AvVzZat2jGrVs3DccDAgLo27sHhfLlokql8hw+dNDo/AXz5jBqxLAoy/c+yq3cH6LcMSe3nW0sxrYuhtuC5nj/2Z7dv9chd9pERmUG/FSA60ta4v1nezaPqEGaJPafXH/3Onnw3dKJsa2LhTuWP4MzW0fVxGtdOx6uacPfY2pjY2UBgJWlBXO7l+Phmjacnd2EkjmSG53bpVYuxrcpHvnAH2AK/R0R5Tat3CuXL6VSuVLkz5WNxg3qcv7ch3MvXbyQ6pUrUCB3diqULsHvo0fh7+9vOP7y5QvG/jaSimVLUSB3dpo2qs+Fc+eM6lg0fy6lihWiVLFCLFowz+jYubNnaFi3JkFBQVEXMgKm1t/BwcHMnTmF+tUqUK5oHhrWqMiiuTMJDQ394HkBAQHMmT6ZelXLUbZwLupVK8+WjX8ajm/dtJ4S+bIabWWL5DaqY8WSBVQvX5zq5YuzculCo2MXz5+ldZO66u+vRLlNK7eYJg3QfWMqVKiAh4cHN2/eZOvWrZQsWZJOnTpRuXJlo3/shg4dioeHB25ubixatAh7e3vKlCnDiBEjInW9WrVqcerUKRYuXMiVK1fYuHEjJUqU4PHjx1GW6dixY3h4eODh4cHatWsBcHNzM+ybNGmS4c8eHh4AzJ8/3/D1sWPHDHW1atUKDw8PLl68SN26dWnfvj3Lly+Psra+bdvWLfw+ZhS/tGvPitV/kj59Btr+0uK99+b0qZP07tGNGjVrs3LNekqWKk3nju1xd79iKDN/7myWL11M/0GDWbJ8Fba2trRt3cLww/Ca1Su5dOECi5atpHaduvTu2c3ww9bdu3dYu2Y1HTt1+Sp5lVu5lfv7yz2jUxlK5XTh59+3k6fdEv45dZvNI2uQxDEOAN1q56Zd1Rz8OnUXxbqs5KVfIH8Nq451LIuP1p07bSJaVMzC2eue4Y7lz+DMhmHV2XnyNkU7r6BIpxXM/OsMrz9ralExCzldE1Ki6yrmbT3Pgp4VDOemSPQDzStkYdDCQ1FzEzCd/lZu0869fesWxo35jV/atmfZ6nWkS5+edr+0xPs9ubdu/ovJE8bxS9v2rNu4mUFDh7N92xamTBpvKDN04AAOHzrI8FGjWfXnRgoWKkybVs159PAhAFfc3JgxbQq/jR3PqDHjmD5lEu5X3AAICgpixNDB9BswBEvLr7doxxT7e/mieWxYu4pOPfqycOUGWnfowvLF81m3atkHzxvStxsnjh+hR/8hLFr9FwOHjSZ5ipRGZeLEsWPtlt2GbeWG7YZj19zdmP/HNAYOH8OAYaOZO3MK16+G3begoCDG/zaMrr0Hqr+VW7lFPpMG6L4xr2exJU2alFy5ctG3b182bNjA1q1bWbBggaFc3LhxcXZ2xsXFhWLFijFr1iwGDBjAwIEDcXNzM5T7999/yZcvH9bW1iROnJjevXsbBvqePHnCvn37GD16NCVLliRFihTky5ePPn36ULVq1SjLlCBBApydnXF2diZ+/PgAJEyY0LAvXrx4hj87OzsDYG9vb/g6QYIEhrpix46Ns7MzqVOnZvDgwaRNm5aNGzdGWVvftnjhfGrWrkv1GrVI4+pK/0FDsLGxYf26tRGWX7pkEYWKFKXZzy1JnSYNHX7tTMZMmVixbAkQ9mnN0sWLaPVLW0qWKkO69BkYPmoMno8esWvnPwDcuHaN4iVL4eqalnoNGuHj7Y2Pjw8AI4YOpnPX7tjZ2X2VvMqt3Mr9feW2sbKgemFX+s3bz4Hz97nu8ZQRS49w7f4TWv2YDYD21XMyesVRNh2+zvmbXrQct4PEjnGoWjDNB+uOYxOL+T3L027yTp688A93fEzrYkzfeJrfVx/n0m1v3O89Ye0+dwKCggFInzw+mw/f4NJtb2ZuOkNC+9g4/WALwOT2Jek/7wDPfQOi7F6YQn8rt3IvWbSAmrXrUK1GLdKkcaXfwP9y/xlx7jOnT5EjZy4q/liFJEmTUbBwESpU+tEwQ87Pz4+d/+ygc9fu5M6TFxeXFLRp35HkLi6sXhn24ejNG9dJmy49+fIXIH+BgqRNl56bN24AsHD+XHLlzkPmrFm/am5T7O/zZ09TpFhJChYpRuIkSSlRuhx58xfi0oVz7z3nyKH9nD55gtETppMnX0ESJ0lK5mw5yJo9p3FBMzMcnZwMW3xHJ8Oh2zdvkDptOnLlzU/ufAVI45qO2zfD+nvlkgVkz5mbDJmyfJXMr5lifyu36eWO6T60Oi46t5hAA3QxQKlSpciePTvr1q37YLlOnToRGhrKhg0bALh37x6VKlUib968nDlzhhkzZjB37lyGDx8OgJ2dHXZ2dqxfv95oOUNMYmtrS0BA1P0S91pgQACXLl6gQMFChn3m5uYUKFCIs2dORXjO2dOnKVCgoNG+QoWLcPb0aQDu3b2Ll5cn+Qu8qTNu3LhkzZbdUGe6DBk4dfIEfn5+HDywnwQJEuDg4MDmTRuxtramdJmyUZzUmHIrt3J/P7ktLcyxtDDHLyDYaL9fQDCFMiUhpfMPJI4fh12nbxuOPXsVwDG3B+TP6PzBuie2K8G2ozfZffpOuGMJ4tmSL0NiPJ/4svv3Otxc2oodo2tRKFMSQ5lzNzwplDkJNlYWlM2dAo/HL/B65kv9EunxDwxm46FrX5j+DVPp73cpt4nlDgzL/XYbzc3NyV+gIGfPnI7wnOw5cnLx4gXDMti7d+5wYO9eihQNW7IeHBxEcHAwVtbWRudZW9tw6uQJAFzTpuPWzZt4eNzn/v173Lp1kzSuablz+zYb16+j/a+dvkLaN0y1v7Nky8GJ40e489+yvKtX3Dh35iT5CxV57zkH9+4hfcZMLF88j9o/luanWpWZPul3/P38jMr5+r6iXtVy1Klchn7dO3Lj2lXDsdSu6bh7+yYPH3jwwOM+d27fJFWatNy7e4etf62nRZuOXyXva6ba38ptWrnFtOklETFEhgwZOPuR9fbx48cnYcKE3Lx5E4Dp06eTPHlypk6dipmZGRkyZOD+/fv06tWLgQPDpp8vWLCAVq1aMXPmTHLlykXx4sWpX78+2bJl++S29erVi/79+xvtCwgIIFOmTJHO+amCg4NZvnw5Z8+epXXr1hGW8ff3DzfwGGphjfU7P2hGxOeJD8HBwTg6Ohrtd3R05MaN6xGe4+XlheNbnzK+Lu/12Ou/42HLwBydwtfp5RVWpnqNWri7uVGjaiUc7B0YM24iz54+ZfrUycydv5ipkyawbesWkiV3YcjwkSRKZPwsqS+l3Mr9uo3KbSwm5n7hG8jhi/fp0yAfbne8efjkFXWLpyN/BmeueTzF2SFsmesjn1dG5z168opE/x2LSJ1i6cjhmpAinVZEeDyVczwA+jXKT5+5+zl7zZNGpTOyZVQNcrddyrX7T1i44yJZUjlxamZjHj/z46dRW3Gws2ZA4wKU77WWQU0KUqdYOq57PKXNxL+5//jlZ98HU+nvdym3ieX2CcsdP1xuJ8OMtndV/LEKPj4+NG/cCAglKCiI2nXr06J1GyBsqWO27DmYPXM6qVKnxtHRiW1bNnP2zGmSu7gAhM1Q6dSFtq1+BqBjp66kTpOGX1o2p3PXHhw8sJ8/pk/D0tKSHr37kjtP3qjNbaL93bBpC16+fEGTulUxN7cgJCSYlm1/pWyFyu895/69u5w7cworK2uGjZnI0yc+TBgzgmdPn9B7YNiH9y4uKenVfyip06bj5YvnrFyykA4tGzN/xZ8kTORMilSpadm2E907hP3s3apdZ1KkSk3X9i35pWMXjh4+wILZM7C0tKRj115kz5UnSnOban8rt2nlFtOmAboYIjQ09JOmZb5d7tKlSxQsWNDovMKFC/PixQvu3r2Li4sLtWrV4scff2Tfvn0cPnyYrVu3MmbMGObMmUOzZs0+qW09evQIV3by5Mns3bv3k/N9qunTpzNnzhwCAgKwsLCgS5cutG3bNsKyo0aNYsiQIUb7+g0YRP+Bg6O8XVElVqxY9B0wyGjfgH59aNioMZcvXWTXrp2sWreBBfPmMHrkcMZPmhJNLY1ayv2Gcit3VOb++fcd/NGlDNeXtCQoOITTVx+x6t8r5HRN+Fn1JXOyY+wvxanc70/8A4MjLGNuHvZvztyt51n890UAzlz3pESO5DQtl4mBCw4SFBxCl+l7ePsJLn90Kcv0jWfIniYBVQqkJl/7pXStnYdxbUrQYMTmz2pvdNL3+RvK/W3mPn70CPNmz6JP/4FkzZaNO7dvM/a3kcyaOZ3WbdoBMHzUGAYP7Ev5UsWxsLAgQ8ZMVKj4I5cuXjDUU6deferUq2/4euOGP4kTOw7ZsuegepWKLFmxmkcPH9C7R1c2b9+JlZXV/z1rVIvu/t79z3b+2baZ/sNGkyp1Gq5ecWPq+NE4OiWgQuVqEZ4TGhqCmZkZ/Yf9hp1dXADadw5gUO+udOnZH2sbGzJny0HmbDkM52TJloMmdavx15+rDbPjqtWqS7VadQ1ltm3aQOzYccicNTuN61TljwXL8Xz0kKH9e7J8/Tb1dwym3G+YQu6oFENWk36TtMQ1hrh06RKpUqX6YJnHjx/j6en50XLvsrGxoWzZsgwYMICDBw/SrFkzBg0a9PET/+Pk5ISrq6vR9vpZc1GtUaNGnD59mhs3bvDy5UvGjx+PuXnE38Z9+vTh6dOnRluPXn0+6ToO9g5YWFiEewDp48ePcXJyivAcJycnHv/36YxR+f8+xXFyCnuW3mOvT6/z6JHDXLvqTv2GP3Hs2FGKFi1G7NixKVehIsePHf2kLJGh3Mr9sTYq9zvlv/HcNx48pVyvtTjWmEbaJnMp2mUlsSzNufHgKQ98wmalJXSIbXROQvvYPPSJeMZazrQJSeQQm0NTGvD8r448/6sjxbIlo13VHDz/qyPm5mZ4eIede+m28b1wu+NN8gRxI6y3WLZkZHKJz4y/zlAsWzK2H7/JK/8g1u67QtGsSb/oHphSf79NuU0st0NY7ndfCPH4sReO72nj9KmT+bFKVWrWrkPadOkpVaYsHTp1Yf6cWYT890aX5C4uzF2whINHT7L1n90sWbGaoKAgkiZLHmGdPj4+zJoxjV59+3Pu3FlSpEhJihQpyZuvAEFBQdy6GfFsvs/ObaL9PXPyOBo2bUHpchVJ7ZqOcpWqULtBY5YunPPecxwdE+CUIKFhcA4gRcrUhIaG4vnoYYTnWFrGIm26DNy7G/5xBgBPnviwcM4Mfu3eh0sXzpHcJQXJXFKQM08+goKCuHv75hflfJep9rdym1ZuMW0aoIsBdu3axblz56hVq9YHy02aNAlzc3OqV68OQMaMGTl06JDRK9cPHDhA3LhxSZYs2XvryZQpEy9ffv5yoq8pXrx4uLq6kjRp0vcOzL1mbW3NDz/8YLR9yvJWgFhWVmTMlJkjh9+8RTAkJIQjRw6R7d2H6f4nW44cHDl82Gjf4UMHyZYjBwBJkyXDySkBR468qfPFixecO3smwjr9/f0ZNXwoAwYPxcIibPnC6xd8BAUGERIS8eyVL6Hcyq3c32fuV/5BPPB5hb2dNWVypWDT4evcfPAMD++XlMz+5hftuLZW5E3vzJFLDyKsZ/fpO+Ruu4T8HZYZthNXHrJiz2Xyd1hGSEgotx4+477XC9IlczA61zWpPbcfPQ9Xp3UsCya2K0GHKbsICQnFwtyMWBZhb5GNZWmOxUf+rv8YU+xvUG6Tyx3rv9xHjHMfPXKYbNlzRHiOn59vuJ+lzC3Cvn77Z0cA29ixSZAgIc+ePuXgwf2UKFUqwjrHjR5Fo8ZNSeTsTEjwm9wQ9niS1wN/UcVU+9vfzw9zM+O+s7CwIDQk9D1nQJbsOXjs6cmrV28ea3Dn9k3Mzc1JkDDiJXrBwcFcv+Yebsnga9MmjKFOg8YkTORMSHDIO/0dRLD6O0oot2nlFtOmAbpvjL+/Pw8ePODevXucPHmSkSNHUq1aNSpXrkyTJk0M5Z4/f86DBw+4c+cOe/fupXXr1gwfPpwRI0bg6uoKQLt27bhz5w4dO3bk8uXLbNiwgUGDBtG1a1fMzc15/PgxpUqVYsmSJZw9e5YbN26wevVqxowZQ7VqEU+PNyWNmzZn3ZpVbFz/J9evXWP40MH4+vpSvUZNAPr16cmkCeMM5Rv91ISDB/axcME8bly/xoxpU7hw/jz1G/4EhL3NplHjJsz+YwZ7du3E/Yob/fv0JEHChJQqXSbc9WfNnE6RYsXJmDHsWX45cuZi5z9/c8XtMiuWLyFHzlzKrdzKrdwfVCaXC2VzpyBFoh8oldOFbaNqceWuN4v+W3o6bf0petXPx4/5U5E5pSNzu5fD4/FLo5c0bBlZkzaVw55L+sI3kIu3HhttL/0C8X7mx8Vbbz6NnrD2BO2q5qBGYVdSJ47HwMYFSJ8sPgu2X+BdfRrkY/uxm5y5HvZcmEMXPahWOA1ZUjrRpkp2Dl28/8X3wVT6W7lNO/dPTZrx55rVbNwQlnvksLDc1aqH5e7fpxeT38pdrHhJVq9czrYtm7l39y6HDx5gxpTJFCteEov/BskPHtjHgf37DMdb/dyUVKlSU/W/Ot92+OABbt26Sb0GjQDInCUrN29cZ/++vaxdvRILc3NSpIzcKo9PYYr9XbBocRYvmMWh/XvxuH+Pfbt3smrZIoqWeDNwOmvaREYO6mv4unT5H/khXjxGD+3PzevXOHPyODMnj6dilRpY29gAsHDODI4dPsj9e3e4cvkiIwb14eEDD36sFn6SwPEjB7l7+xbV6zQAIH2mzNy+dYMjB/fx15+rMTe3wMUlZZRnN8X+Vm7Tyx3TRffbWmPyW1z1DLpvzLZt20icODGWlpY4ODiQPXt2Jk+eTNOmTY0+5Rw4cCADBw7EysoKZ2dnChQowM6dOylZsqShTNKkSdmyZQs9evQge/bsxI8fnxYtWhhe6GBnZ0f+/PmZMGEC165dIzAwkOTJk9OqVSv69u0brm2mpkLFSvh4ezN96mS8vDxJnyEj0/+YY1gq8sDDw+jTyxw5czFqzO9MnTyRKRPH45IiJROnTCNt2nSGMs1btMLX15ehgwfy/PkzcubKzfQ/5oSb2efufoUd27aycu16w76y5Spw/OhRmjdpRIqUqfhtzDi+BuVWbuX+fnLHi2PN0GaFSOpkh/dzfzYcuMqghWHPgAMYt+YEsW1iMbVjaeztrDl44T5VB643er5c6sTxcIxnG6nrTt1wGhsrS8a0LoZDXBvOXfekcr8/ufHgqVG5TCkcqVU0Hfk7LDXsW7ffnaJZk/HP2Nq43/Wh6ZhtX3AHwphKfyu3aecuX7ESPj7ezJg6hcf/5Z42c/Zbue8bnhEJ0PKXtpiZmTF9yiQePXqIg0N8ipUoSYdfOxvKvHj+gikTx/Pw4QPixbOndNmytP+1C7FixTK6tp+fH7+NHMbo3ycYfl5N5OxMzz79Gdy/L7GsrBg64jds/hsIikqm2N+duvdl7h9TmThmOD4+3jg5JaBKjdo0bfnmucyPvTx5+NDD8HXs2LH5feosJv8+il+a1ueHePEoWaa80ZtXnz97xu8jB+P92Au7uD+QPmMmps1ZTMrUaYyu7+/nx6Sxoxg4cqyhvxMmcubXbn34begArKys6DNohGHgLyqZYn8rt+nlFtNlFvruHHaR75hf0MfLiIjEJA5VJ0V3E6KFz8ZO0d0Eka8uxER/TDePITMdoprPy4DobkK0cIgT818kIfIxNiY0NarU5EMfLxQNdv1aMLqb8FEm9G0iIiIiIiIiIiJfi4l+xhIl9Aw6ea+lS5diZ2cX4ZY5c+bobp6IiIiIiIiIyHdBM+jkvapWrUr+/PkjPPbus0dEREREREREROTzaIBO3itu3LjEjRs3upshIiIiIiIiIjGAqT5HNCpoiauIiIiIiIiIiEg00gCdiIiIiIiIiIhINNISVxERERERERER+WJa4fr5NINOREREREREREQkGmmATkREREREREREJBppiauIiIiIiIiIiHwxM61x/WyaQSciIiIiIiIiIhKNNEAnIiIiIiIiIiISjbTEVUREREREREREvpi5Vrh+Ns2gExERERERERERiUYaoBMREREREREREYlGWuIqIiIiIiIiIiJfTG9x/XyaQSciIiIiIiIiIvKWadOmkTJlSmxsbMifPz9Hjx79YPknT57Qvn17EidOjLW1NenSpWPLli2ffD3NoBMREREREREREfnPypUr6dq1KzNnziR//vxMnDiR8uXL4+bmRsKECcOVDwgIoGzZsiRMmJA1a9aQNGlSbt26hb29/SdfUwN0IiIiIiIiIiLyxb6XFa7jx4+nVatWNG/eHICZM2eyefNm5s2bR+/evcOVnzdvHt7e3hw8eJBYsWIBkDJlykhdU0tcRURERERERETku+Xv78+zZ8+MNn9//wjLBgQEcOLECcqUKWPYZ25uTpkyZTh06FCE52zcuJGCBQvSvn17EiVKRJYsWRg5ciTBwcGf3EbNoBMREYnBfDZ2iu4mRAuHCr9FdxOihc+28J/YmoJnvoHR3YRo8YNtrOhugvwfOcSxiu4miIh8t0aNGsWQIUOM9g0aNIjBgweHK+vl5UVwcDCJEiUy2p8oUSIuX74cYf3Xr19n165dNGrUiC1btnD16lXatWtHYGAggwYN+qQ2aoBORERERERERES+mBnf5hrXPn360LVrV6N91tbWUVZ/SEgICRMmZNasWVhYWJA7d27u3bvH2LFjNUAnIiIiIiIiIiJibW39yQNyTk5OWFhY8PDhQ6P9Dx8+xNnZOcJzEidOTKxYsbCwsDDsy5gxIw8ePCAgIAArq4/PktYz6ERERERERERERAArKyty587Nzp07DftCQkLYuXMnBQsWjPCcwoULc/XqVUJCQgz7rly5QuLEiT9pcA40QCciIiIiIiIiIlHA3Ozb3CKra9euzJ49m4ULF3Lp0iXatm3Ly5cvDW91bdKkCX369DGUb9u2Ld7e3nTq1IkrV66wefNmRo4cSfv27T/5mlriKiIiIiIiIiIi8p969erh6enJwIEDefDgATly5GDbtm2GF0fcvn0bc/M3c96SJ0/O9u3b6dKlC9myZSNp0qR06tSJXr16ffI1zUJDQ0OjPInIN8ovKLpbICIiUUFvcTUteouriIjEZDYmNDWq6qxj0d2ECG1snTe6m/BRJvRtIiIiIiIiIiIiX4uZ2bf5FteYQM+gExERERERERERiUYaoBMREREREREREYlGWuIqIiIiIiIiIiJfTCtcP59m0ImIiIiIiIiIiEQjDdCJiIiIiIiIiIhEIy1xFRERERERERGRL2auNa6fTTPoREREREREREREopEG6ERERERERERERKKRlriKiIiIiIiIiMgX0wrXz6cZdCIiIiIiIiIiItFIA3QiIiIiIiIiIiLRSEtcRURERERERETki5lpjetn0wy6GKZZs2aYmZlhZmZGrFixSJQoEWXLlmXevHmEhIQYyqVMmdJQztbWlpQpU1K3bl127doV6Wt6enrStm1bXFxcsLa2xtnZmfLly3PgwIEPnrdnzx5DG9637dmzB4C1a9dSokQJ4sWLh52dHdmyZWPo0KF4e3sDsGDBAsM55ubmJEuWjObNm/Po0aNI54mMFcuWUrFsKfLmzEqj+nU4d/bsB8vv2L6VapUrkDdnVmpVr8K+vf8aHQ8NDWXalEmULl6EfLmy0bpFM27dumk4HhAQQN/ePSiULxdVKpXn8KGDRucvmDeHUSOGRVm+91Fu5f4Q5Vbut32Lue1srRjbtjRuS9vivbkbuyf9RO70zgBYWpgzvGUJjs3+Ga+/unJ9RXvm9KpMYke7z67zbeldHFk9tBYPNnTG66+u7J/WlOQJfzAcH92mFPfWdcJ9WTvql8pkdG7NYulZM6x2FNyBN0yhv99Vp0o5iubJEm4bP3r4e8/Z/c92GtWqQulCuWharwaH9u99b9nfRw6haJ4srFq22LAvICCAYQN6U754fhrU/JHjRw4ZnbNs0TwmjBn55eE+whT7G5RbuZU7Isods3OLadIAXQxUoUIFPDw8uHnzJlu3bqVkyZJ06tSJypUrExQUZCg3dOhQPDw8cHNzY9GiRdjb21OmTBlGjBgRqevVqlWLU6dOsXDhQq5cucLGjRspUaIEjx8//uB5hQoVwsPDw7DVrVvX0PbXW6FChejXrx/16tUjb968bN26lfPnzzNu3DjOnDnD4sVvfvj94Ycf8PDw4O7du8yePZutW7fSuHHjyN28SNi2dQu/jxnFL+3as2L1n6RPn4G2v7R4b+7Tp07Su0c3atSszco16ylZqjSdO7bH3f2Kocz8ubNZvnQx/QcNZsnyVdja2tK2dQv8/f0BWLN6JZcuXGDRspXUrlOX3j27ERoaCsDdu3dYu2Y1HTt1+WqZlVu5lVu5v4fcM7pVpFTulPz82ybytJrLPydusnlMfZI42hHbJhY50ibityUHKdh2AfWH/Em6ZPFZPbTWZ9f5WqrE9uyc+BNX7jymfLfl5G09j1FLDuAXEPZvc6UCrtQtlYkqvVfSb/ZupneriOMPtgD8EMeawT8Xp8uUHVF2H0ylv981a9EK1m/bY9gmTJsNQMnS5SIsf+7MKYb068mP1Wowd+lqipYoRd/uv3L9qnu4snt3/8OF82dxSpDQaP/Gdatxu3yRmfOWUrVGbYb072XIff/eXf5av5bW7X6N4qTGTLW/lVu5lVu5v7fcYro0QBcDvZ7FljRpUnLlykXfvn3ZsGEDW7duZcGCBYZycePGxdnZGRcXF4oVK8asWbMYMGAAAwcOxM3NzVDu33//JV++fFhbW5M4cWJ69+5tGOh78uQJ+/btY/To0ZQsWZIUKVKQL18++vTpQ9WqVT/YTisrK5ydnQ2bra2toe2vt9OnTzNy5EjGjRvH2LFjKVSoEClTpqRs2bKsXbuWpk2bGuozMzPD2dmZJEmSULFiRX799Vf++ecffH19o/YG/2fxwvnUrF2X6jVqkcbVlf6DhmBjY8P6dWsjLL90ySIKFSlKs59bkjpNGjr82pmMmTKxYtkSIOzTmqWLF9Hql7aULFWGdOkzMHzUGDwfPWLXzn8AuHHtGsVLlsLVNS31GjTCx9sbHx8fAEYMHUznrt2xs/vwLA/lVm7lVm5Tzm1jZUn1ounpN3sPB87d4fr9J4xYtJ9r957QqmpOnr30p3Kvlaz99zLud705euk+XabuIHf6xEYz3SJT52tDfi7G9iPX6Dd7D2euPuSGxxM2H7qK55NXAGRwcWTfmducvPKAVbsv8exVACkTxwu7F61KMPuvU9x59CzK7oUp9HdEHBzi4+jkZNgO7v+XpMmSkyN33gjLr1mxhHwFC9Owyc+kTJWGlm07ki5DJtatWmZUzvPRQyaOHcXAYaOxtDR+Ssytm9cpUqwkqdK4UrNOA574ePPkSVjucb8No23HLsTRf9/KrdzKrdzKbQLMzL7NLSbQAN13olSpUmTPnp1169Z9sFynTp0IDQ1lw4YNANy7d49KlSqRN29ezpw5w4wZM5g7dy7Dh4ctA7Gzs8POzo7169cbPlWISkuXLsXOzo527dpFeNze3v6959ra2hISEmI0azCqBAYEcOniBQoULGTYZ25uToEChTh75lSE55w9fZoCBQoa7StUuAhnT58G4N7du3h5eZK/wJs648aNS9Zs2Q11psuQgVMnT+Dn58fBA/tJkCABDg4ObN60EWtra0qXKRvFSY0pt3Irt3K/LSbmtrQwx9LC3DBr7TW/gEAKZUke4Tk/xLEmJCSUJy/8PrtOMzOokD8N7ne92fhbXW6t7sjeKU2oUiitofzZ64/IlS4x9nbW5EybCFsrS67d86FQlmTkTOvMtD+Pf0l0I6bS3x8TGBjIji2bqFS1xnufiXP+7Bny5DPOna9gIc6fO2P4OiQkhOED+9CgcTNSpXENV4dr2vScPX0Sfz8/jhw+gKNTAuztHdixdRNWVtYUK1kmaoO9w1T7W7mVW7mV+23fQ24xbXpJxHckQ4YMnP3Imvz48eOTMGFCbt68CcD06dNJnjw5U6dOxczMjAwZMnD//n169erFwIEDsbS0ZMGCBbRq1YqZM2eSK1cuihcvTv369cmWLdsXt9nd3Z3UqVMTK1asSJ83c+ZM8uTJQ9y4cSMs4+/vH25QMdTCGmtr64/W7/PEh+DgYBwdHY32Ozo6cuPG9QjP8fLywtHRKVx5r8de/x33DNvnFL5OL6+wMtVr1MLdzY0aVSvhYO/AmHETefb0KdOnTmbu/MVMnTSBbVu3kCy5C0OGjyRRokQfzRIZyq3cr9uo3MaU+51M33DuF74BHL5wlz4/Fcbt9mMe+rykbslM5M+YlGv3fcKVt45lwfCWJVm1+yLPXwV8dp0J7eMQN7Y13esXYMiCffSfvYdyeVOzYnBNyndfxv6zd/jn+A2W77zA/mnN8A0IpNWYzbz0C2RSp3K0HrOZ1lVy0rZ6bh4/9aX9hG1cuuX12ffBVPr7Y/bt2cmLF8+pVKX6e8t4P/YifnzjTPHjO+H9+M39X7pwLhYWFtSu/1OEdfxYrQbXrl6hcd1qxLO3Z+hv43j+7BlzZ05l8h/zmT19Mjt3bCVJsuT0GTiMBAn133dUUG7lft1G5Tam3O9kikG5xbRpgO47Ehoa+klvTHm73KVLlyhYsKDReYULF+bFixfcvXsXFxcXatWqxY8//si+ffs4fPgwW7duZcyYMcyZM4dmzZp9cZs/1dOnT7GzsyMkJAQ/Pz+KFCnCnDlz3lt+1KhRDBkyxGhfvwGD6D9w8Oc296uLFSsWfQcMMto3oF8fGjZqzOVLF9m1ayer1m1gwbw5jB45nPGTpkRTS6OWcr+h3Mqt3F+e++ffNvFH90pcX9mBoOAQTrs/YNXui+RMa/xSB0sLc5YMqI6ZGfw6afsX1WluHvbv6KZD7kxZewyAs9cekT9TUlpVzsn+s3cAGLFoPyMW7TfU27dxYXafvEVgUAi9GhUib6u5VCzgypxelSncbsEX34v/t2/t+3zThnXkL1Qk3DPjIsPt0gXWrFjC3CWr3/tzlqVlLLr26m+0b+SQ/tSu3wh3t8vs27OL+cvXsmzRPCaNHcXwsRM/uz3fkm+tv/9flPsN5VZu5f4+ckcl85iynvQbpCWu35FLly6RKlWqD5Z5/Pgxnp6eHy33LhsbG8qWLcuAAQM4ePAgzZo1Y9CgQR8/8SPSpUvH9evXCQwM/GjZuHHjcvr0ac6fP8/Lly/Zu3cv6dKle2/5Pn368PTpU6OtR68+n9QuB3sHLCwswj2A9PHjxzg5OUV4jpOTE48fe4Uv/9+nOE5OCcL2eX16nUePHObaVXfqN/yJY8eOUrRoMWLHjk25ChU5fuzoJ2WJDOVW7o+1UbnfKa/cYfu+sdw3PJ5QrtsyHCuPI22DaRTtsIhYlhbcePDEUMbSwpylA6rjkigelXuteO/suU+t0+vpKwKDgrl0y/heuN1+/N5n26VLHp8GpTMzZP5eimV34cC5O3g99WXtv5fJlc4ZO1urz74HptTf7/PA4z4njh6mcrUPvwAkvqMT3t7Gmby9vYj/X+4zp07i4+1N7cplKZE/OyXyZ+eBx32mTRxLnSoRv3ji5PGj3Lx2lZp1G3LqxDEKFC6KrW1sSpWpwKmTx6Im4FtMtb+VW7k/1kblfqe8coft+4Zzi2nTAN13YteuXZw7d45atT78Q+ikSZMwNzenevXqAGTMmJFDhw4ZzWQ7cOAAcePGJVmyZO+tJ1OmTLx8+fKL292wYUNevHjB9OnTIzz+5MkTw5/Nzc1xdXUlderU2NrafrRua2trfvjhB6PtU5a3AsSysiJjpswcOXzIsC8kJIQjRw6RLXvOCM/JliMHRw4fNtp3+NBBsuXIAUDSZMlwckrAkSNv6nzx4gXnzp6JsE5/f39GDR/KgMFDsbCwICQk2PC8vaDAIEJCgj8pS2Qot3Irt3K/LabnfuUXyAPvl9jbWVMmTyo2HQx7K+frwbk0SR34sedyvJ9F/Oy5yNQZGBTCCTcP0iWLb1Q+bbL43H70NMK6pnauQK+Zu3jpF4iFhTmxLCwAiGUR9uOZhfnnfwJtiv39ri0b/8TeIT4FixT7YLks2bJz4phx7uNHDpEla3YAyleqwoLl65i3dI1hc0qQkAaNmzNuyh/h6vP392f86OF07zsofO6gIEKCQ6Io4Rum2t/KrdzKrdxv+x5yi2nTAF0M5O/vz4MHD7h37x4nT55k5MiRVKtWjcqVK9OkSRNDuefPn/PgwQPu3LnD3r17ad26NcOHD2fEiBG4uoY94Lhdu3bcuXOHjh07cvnyZTZs2MCgQYPo2rUr5ubmPH78mFKlSrFkyRLOnj3LjRs3WL16NWPGjKFatWpfnCV//vz07NmTbt260bNnTw4dOsStW7fYuXMnderUYeHChV98jc/VuGlz1q1Zxcb1f3L92jWGDx2Mr68v1WvUBKBfn55MmjDOUL7RT004eGAfCxfM48b1a8yYNoUL589Tv2HY82rMzMxo1LgJs/+YwZ5dO3G/4kb/Pj1JkDAhpUqHf3j0rJnTKVKsOBkzZgIgR85c7Pznb664XWbF8iXkyJlLuZVbuZVbuSNQJk8qyuZNRQrneJTKlZJtvzfkyp3HLNp2DksLc5YNqkGudM40H/UXFubmJHKIQyKHOMSyfPNj0ZYx9WlTLdcn1fnahFVHqV0iI80rZSd1EnvaVMtFpYKuzNoY/mHWzStlx+vpK7YcvgrAofN3KZ7ThXwZk9CxVl4u3vTk6csvezmTqfR3REJCQtjy13oqVq4W7o2rwwf2YebUCYava9f/iSMHD7BiyQJu3bzOvD+mcfniBWrWbQhAPHt7UrumNdosLS2J7+iES8rwKxIWzplJwcJFSZchIwBZs+dk7+5/uOruxtpVy8iSPcdXyWyq/a3cyq3cyv295Y7pzL7RLSbQM+hioG3btpE4cWIsLS1xcHAge/bsTJ48maZNm2Ju/uaXi4EDBzJw4ECsrKxwdnamQIEC7Ny5k5IlSxrKJE2alC1bttCjRw+yZ89O/PjxadGiBf37hz1Hxc7Ojvz58zNhwgSuXbtGYGAgyZMnp1WrVvTt2zdK8owePZrcuXMzbdo0Zs6cSUhICGnSpKF27do0bdo0Sq7xOSpUrISPtzfTp07Gy8uT9BkyMv2POTj+N/35gYcH5mZv7neOnLkYNeZ3pk6eyJSJ43FJkZKJU6aRNu2bZbjNW7TC19eXoYMH8vz5M3Lmys30P+aEm9nn7n6FHdu2snLtesO+suUqcPzoUZo3aUSKlKn4bcw4vgblVm7lVu6YnjteHGuGtihOUqe4eD/3Y8M+NwbN30tQcAguieIZ3qx6dNbPRueV67aMfWduA5A6iQOO8WJ/Up2vbTxwhY6TttOjfgHGtS/DlTveNBjyJwfP3zW6TkL72PRqWIiSnRYb9h1382DS6mOsG1EHT5+XtBqz+Yvvg6n0d0SOHz3EwwceVKpaI9yxhw88MHvr56Ws2XMyaMRoZk+fwqxpk0iWPAUjf59Mate04c79mOtX3dn9z3bmLVtj2FeidDlOnThGh5ZNcUmRkoEjxnxeqI8w1f5WbuVWbuX+3nKL6TILjcxT+kViOL+g6G6BiIhEBYcKv0V3E6KFz7be0d2EaPHM9+PPqv0e/WAbubfci4jIt8nGhKZG1V8YfuXAt2BF04iXRn9LTOjbREREREREREREvpb3vfFcPk7PoJMvsnTpUuzs7CLcMmfOHN3NExERERERERH55mkGnXyRqlWrkj9//giPxYqlZRkiIiIiIiIiIh+jATr5InHjxiVu3LjR3QwRERERERERiWbmWuH62bTEVUREREREREREJBppgE5ERERERERERCQaaYmriIiIiIiIiIh8Mb3F9fNpBp2IiIiIiIiIiEg00gCdiIiIiIiIiIhINIr0AN3ChQvZvHmz4euePXtib29PoUKFuHXrVpQ2TkRERERERERE5HsX6QG6kSNHYmtrC8ChQ4eYNm0aY8aMwcnJiS5dukR5A0VERERERERE5NtnZvZtbjFBpF8ScefOHVxdXQFYv349tWrVonXr1hQuXJgSJUpEdftERERERERERES+a5GeQWdnZ8fjx48B2LFjB2XLlgXAxsYGX1/fqG2diIiIiIiIiIjIdy7SM+jKli1Ly5YtyZkzJ1euXKFSpUoAXLhwgZQpU0Z1+0REREREREREJAYwiynrSb9BkZ5BN23aNAoWLIinpydr167F0dERgBMnTtCgQYMob6CIiIiIiIiIiMj3LNIz6Ozt7Zk6dWq4/UOGDImSBomIiIiIiIiIiJiSTxqgO3v27CdXmC1bts9ujIiIiIiIiIiIxEzmWuH62T5pgC5HjhyYmZkRGhoa4fHXx8zMzAgODo7SBoqIiIiIiIiIiHzPPmmA7saNG1+7HSIiIiIiIiIiIibpkwboUqRI8bXbISIiIiIiIiIiMZje4vr5Iv2SCIDFixczc+ZMbty4waFDh0iRIgUTJ04kVapUVKtWLarbKCLyWV74BUV3E6KFnc1n/dUe4y09eTu6mxAtGuVyie4mRAufbb2juwnRotnSU9HdhGixoFHO6G6CiIiIyFdlHtkTZsyYQdeuXalUqRJPnjwxPHPO3t6eiRMnRnX7REREREREREREvmuRHqCbMmUKs2fPpl+/flhYWBj258mTh3PnzkVp40REREREREREJGYw+0a3mCDSA3Q3btwgZ87wywysra15+fJllDRKRERERERERETEVER6gC5VqlScPn063P5t27aRMWPGqGiTiIiIiIiIiIiIyYj0k8S7du1K+/bt8fPzIzQ0lKNHj7J8+XJGjRrFnDlzvkYbRURERERERETkG2eut7h+tkgP0LVs2RJbW1v69+/Pq1evaNiwIUmSJGHSpEnUr1//a7RRRERERERERETkuxXpATqARo0a0ahRI169esWLFy9ImDBhVLdLRERERERERETEJHzWAB3Ao0ePcHNzA8DMzIwECRJEWaNERERERERERCRm0QrXzxfpl0Q8f/6cxo0bkyRJEooXL07x4sVJkiQJP/30E0+fPv0abRQREREREREREfluRXqArmXLlhw5coTNmzfz5MkTnjx5wqZNmzh+/Di//PLL12ijiIiIiIiIiIjIdyvSS1w3bdrE9u3bKVKkiGFf+fLlmT17NhUqVIjSxomIiIiIiIiISMxgpjWuny3SM+gcHR2JFy9euP3x4sXDwcEhSholIiIiIiIiIiJiKiI9QNe/f3+6du3KgwcPDPsePHhAjx49GDBgQJQ2TkRERERERERE5Hv3SUtcc+bMaTRN0d3dHRcXF1xcXAC4ffs21tbWeHp66jl0IiIiIiIiIiImSCtcP98nDdBVr179KzdDRERERERERETENH3SAN2gQYO+djtERERERERERERMUqTf4ioiIiIiIiIiIvIuc61x/WyRHqALDg5mwoQJrFq1itu3bxMQEGB03NvbO8oaJyIiIiIiIiIi8r2L9FtchwwZwvjx46lXrx5Pnz6la9eu1KxZE3NzcwYPHvwVmigSsRIlStC5c+foboaIiIiIiIiIyBeJ9ADd0qVLmT17Nt26dcPS0pIGDRowZ84cBg4cyOHDh79GG+UTNWvWDDMzM8zMzLCyssLV1ZWhQ4cSFBQU3U2LsVYsW0rFsqXImzMrjerX4dzZsx8sv2P7VqpVrkDenFmpVb0K+/b+a3Q8NDSUaVMmUbp4EfLlykbrFs24deum4XhAQAB9e/egUL5cVKlUnsOHDhqdv2DeHEaNGBZl+d7H1HLP/WMahXNnNtoa1Kz8wXNWLltE/Zo/UrJQLmpUKs2kcb/h7+9vOB4cHMys6ZOpXaUcJQvlok7VCsyfPYPQ0FBDmWWL5vNjmaL8WKYoyxcvMKr/wrmz/Nyozv/lv9/vvb9P/fMX8/u2ZmKrakxsVY0lQ37l+pmjhuMvnnizaeZvTOtQlwktqrCgf1vcju37YJ13Lp9l7bgBTOtYjzGNy+J+/EC4Mlv+GMOYxmWNttVj+hiOBwUGsGnmb0xsVY3ZPZpx8/xJo/OPbF7FP4umfmH68L73/n6f7z137ezOrGia02gbVz2j4fjA8q7hjrcokPyDdcazsaRtYRem18nCwkbZ6V0mDc5xrQ3HE8SxClfn6y1/CnsA4lhZ0KNUahY0zMaoyulJGd/W6BrN8yfjx0wJo+w+vPa99/f7KLdyf4hyK/fblPvbzh2TmZl9m1tMEOkBugcPHpA1a1YA7OzsePr0KQCVK1dm8+bNUds6ibQKFSrg4eGBu7s73bp1Y/DgwYwdOza6m/XZQkNDo22AcdvWLfw+ZhS/tGvPitV/kj59Btr+0oLHjx9HWP70qZP07tGNGjVrs3LNekqWKk3nju1xd79iKDN/7myWL11M/0GDWbJ8Fba2trRt3cIwsLNm9UouXbjAomUrqV2nLr17djMM6Ny9e4e1a1bTsVMX5f4KUqVxZeP2PYZtxtzF7y27Y+smZk6ZwM+t2rJszV/0HjCUnTu28ce0iYYySxbOZf2alXTt2Y9la/6i3a9dWLpoHmtWLAXgqrsbc2ZOZejIsQwZOZZZMyZz7b97FhQUxNhRQ+jRdyCWll/3UaGm0N9x4ztRrG4LmgybRpOh03DJlIN1EwbhdfcmAFv+GI23x11qdhlK81GzSJenCBunDOfhzavvrTPQ34+ELqkp27TjB6+dKlte2k1ZadiqtO9rOHZm9xYe3nDnp0GTyF7iRzZNH2W4D08eeXB2zxaK1mn+5TfgLabQ36ac+46PL7+sPGfYBm+9YnR85xUvo+PLTtz7YH3dSqYmYVxrft91nd5/XcbrRQD9yrlibRn246PXqwCj+n5ZeY5VpzzwDQzm9L1nANTI5oxtLHP6bHLj0sMXtCroYqjf1Sk2rk5x2HLpUZTeB1Ppb+VWbuVWbuX+PnOL6Yr0AF2yZMnw8PAAIE2aNOzYsQOAY8eOYW1t/aFT5f/A2toaZ2dnUqRIQdu2bSlTpgwbN25k/PjxZM2alThx4pA8eXLatWvHixcvDOfdunWLKlWq4ODgQJw4ccicOTNbtmwBwMfHh0aNGpEgQQJsbW1JmzYt8+fPB6B27dp06NDBUE/nzp0xMzPj8uXLQNgnEHHixOGff/4BwN/fn19//ZWECRNiY2NDkSJFOHbsmOH8PXv2YGZmxtatW8mdOzfW1tbs37+fly9f0qRJE+zs7EicODHjxo376vdy8cL51Kxdl+o1apHG1ZX+g4ZgY2PD+nVrIyy/dMkiChUpSrOfW5I6TRo6/NqZjJkysWLZEiBssHHp4kW0+qUtJUuVIV36DAwfNQbPR4/YtTPs/ty4do3iJUvh6pqWeg0a4ePtjY+PDwAjhg6mc9fu2NnZKfdXYGFhgaNTAsNm7+Dw3rLnzp4ma/aclKtYmcRJkpK/YGHKlq/EpfPnDGXOnzlN0RKlKFS0OImTJKVkmfLkK1CIixfCyty6cYM0adORO18B8uQrgKtrOm7dvAGEzazLkTMPGTNn/aqZwTT62zVXQdLkyE9852TET5yMYnV+xsrGlvtXLwFwz/0iuctWI3GaDNgnTEyh6o2wjhOHBzevvLfO1NnzUbROc9LlKfLBa1tYxsLOPr5hs4kT13Ds8f3buOYqiFOylOQsW5VXz5/g+zzsQ6+/F0ymeL2WWNvGiYI78IYp9Lcp5w4ODeWpX5Bhe+4fbHTcPyjE6LhvYMh760r8gzXpEsZh7uE7XH/8Co9n/sw9fAcrCzMKpXL47z5gVN9TvyDyusTj8M0n+AeF1Z00njUHb/jg8cyff654kTRe2M+KFmbQsmBy5h6+zVsTi6OEqfS3ciu3ciu3cn+fucV0RXqArkaNGuzcuROAjh07MmDAANKmTUuTJk34+eefo7yB8mVsbW0JCAjA3NycyZMnc+HCBRYuXMiuXbvo2bOnoVz79u3x9/dn7969nDt3jtGjRxv+4hkwYAAXL15k69atXLp0iRkzZuDk5ARA8eLF2bNnj6Gef//9FycnJ8O+Y8eOERgYSKFChQDo2bMna9euZeHChZw8eRJXV1fKly8f7uUivXv35rfffuPSpUtky5aNHj168O+//7JhwwZ27NjBnj17OHnSeDlYVAoMCODSxQsUKFjIsM/c3JwCBQpx9sypCM85e/o0BQoUNNpXqHARzp4+DcC9u3fx8vIkf4E3dcaNG5es2bIb6kyXIQOnTp7Az8+Pgwf2kyBBAhwcHNi8aSPW1taULlM2ipMaM9XcAHdv36Zq+RLUqVqewf168sDj/nvLZs2WA7dLF7l4PmyK/b27dzh0YB8FihQzlMmSPQfHjx7m9n9T5t2vXObs6VMUKFQUgDRp03Ln9k0eeNzngcd97ty+RWpXV+7euc2Wv/6kVbtfv17Y/5hif4eEBHPp0G4C/f1IkjYTAEnTZuLSkX/xffGM0JAQLh3aTXBAIC4Zs3/x9e5cPsPUdnWY3aM5O+ZPwvf5M8OxhC6puXvlPIEB/tw8e5w49vGxjRuPCwd2YhHL6qODf5Fliv0NppXbOa410+tkYVLNTHQomgLHOLGMjhdJ7cCselkZWzUD9XMlxsri/es9LM3DjgUGvxnECwWCQkLJkDDigeNU8W1J5Rib3e5vZjbc8vElc+K4mJtB9iQ/cNvHD4AqWRJx8cELrj/2/dy4ETKl/n6bciu3civ325T7jZiW+3vw+rFb39oWE0R67dRvv/1m+HO9evVIkSIFBw8eJG3atFSpUiVKGyefLzQ0lJ07d7J9+3Y6duxo9DKFlClTMnz4cNq0acP06dMBuH37NrVq1TIsX06dOrWh/O3bt8mZMyd58uQxnP9aiRIl6NSpE56enlhaWnLx4kUGDBjAnj17aNOmDXv27CFv3rzEjh2bly9fMmPGDBYsWEDFihUBmD17Nn///Tdz586lR48ehnqHDh1K2bJhf/m9ePGCuXPnsmTJEkqXLg3AwoULSZYsWdTfuP/4PPEhODgYR0dHo/2Ojo7cuHE9wnO8vLxwdHQKV97rsdd/xz3D9jmFr9PLK6xM9Rq1cHdzo0bVSjjYOzBm3ESePX3K9KmTmTt/MVMnTWDb1i0kS+7CkOEjSZQoUZTkfc1Uc2fKko1+g0fgkjIljz09mTd7Bu1aNmHxqg3EiRP+F9FyFSvz9MkT2rZoTGgoBAcHUb1WPZr+3NpQpnGzlrx68YKGtSpjbm5BSEgwrdt1onylsGfbpUyVhl/ad6Zz+1YA/NKhMylTpaFT2xa0+7UbRw/tZ+6s6VhaWtK5ex9y5MoTpZnBtPrb884Nlgz5laDAAKxsbKneaRBOSVMAULXDADZOG86UtrUwt7DA0sqa6p0H4ZAo6RddM1W2vKTNWwT7BIl58vA+e1fPY/Xvfflp0CTMzS3IWqwCnrevM69XS2zj/kC1DgPwe/mcA+sWUr/v7+xbPZ9Lh/dgnygxFVt2J258p49f9ANMqb/fZiq5r3q9YsaB23g888PeNha1szszuEI6emy4hF9QCAeu++D5MgCfV4G4ONjSMHcSkvxgw/g9NyKs7/5TPzxfBFA/VxLmHLqDX1AIP2ZKgGMcK+xtY0V4Tsm0jtx94ssVz5eGfRvOPaRlgeRMqpkZzxf+/HHwNs5xrSmeJj4Dtl6hRYHkZEsSl+uPXzHr4O0Pzur7FKbS3+9SbuV+3UblNqbc72RS7rB933BuMW1f/HCjAgUKUKBAAR49esTIkSPp27fvx0+Sr2bTpk3Y2dkRGBhISEgIDRs2ZPDgwfzzzz+MGjWKy5cv8+zZM4KCgvDz8+PVq1fEjh2bX3/9lbZt27Jjxw7KlClDrVq1yJYtGwBt27alVq1anDx5knLlylG9enXDjLgsWbIQP358/v33X6ysrMiZMyeVK1dm2rRpQNiMuhIlSgBw7do1AgMDKVy4sKG9sWLFIl++fFy6dMkox+vBwNfnBQQEkD9/fsO++PHjkz59+g/eC39/f6OH9gOEWlh/00uxY8WKRd8Bg4z2DejXh4aNGnP50kV27drJqnUbWDBvDqNHDmf8pCnR1NKoFd25CxYuaviza9r0ZMqajVo/lmXX39uoUr1WuPInjx9l0fxZdOs9gMxZsnH3zm0m/T6K+bNn0LxVWwB2/b2NHds2M3jEGFKldsX9ymUmjfsNpwQJqFSlOgA1atejRu16hnq3/LWe2LHjkCVbdhrUrMycxSt59PABA/t0Z81fO7CysorS3NElOvo7fuJkNBsxE/9XL3E7uo8ts8bSoN84nJKmYP/aBfi/fEm93qOxtYuH+4mDbJw6nIb9J5AgearPvmbGgiUNf06QPBUJXFIzq1sT7lw6Q4rMubCwtKRsM+OZkltmjSVXueo8vHUV9xMHaTZiJkc3r2Ln4mlU7zTo3UvECNH933d0+X/nfv3MN4DbPn5c9XzF1NqZKZjSnt1Xvdn51qy2O0/8eOIbyIDyaUkU14qHzwPC1RccCuN3X+eXwi7MbZCN4JBQznk859Tdp5gR/lPoWBZmFE7twLozD432+waGMGXfLaN9/cu5suTEfYqkik+iuFZ0/fMirQu5UCt7YpYc//Bz8b5V+j5/Q7mVW7mVOyYz1dzybYj0Etf38fDwYMCAAVFVnXymkiVLcvr0adzd3fH19WXhwoV4enpSuXJlsmXLxtq1azlx4oRhAC0gIOyH8pYtW3L9+nUaN27MuXPnyJMnD1OmhP1lU7FiRW7dukWXLl24f/8+pUuXpnv37kDY9NVixYqxZ88ew2BctmzZ8Pf35/z58xw8eJDixYtHOkdEs5Yia9SoUcSLF89oGzt61Ced62DvgIWFRbgHkD5+/NiwvPddTk5OPP7v0xmj8v99iuPklCBsn9en13n0yGGuXXWnfsOfOHbsKEWLFiN27NiUq1CR48eORnjOlzDV3O+KG/cHkqdIwd07tyM8PnvGFMpXqkrVGrVJkzYdxUuV4ZcOnVk8fw4hIWGzP6ZNGsdPzVpQpnwl0qRNR4Ufq1KvYRMWz58TYZ1PfHyYP3sGXXr25cL5syRPkYLkLinInTc/wUFB3Hnr7VJRxZT628IyFg6JkuKcKh3F67UgoUtqTmz/E5+H9zn59wYqtupGisy5SJgiDYVrNsY5VTpO/rMhSq79mn3CxNjGjYfPw4iXT9+6eBqve7fIVbYady6dJXX2fFjZ2JIhf3FuXz7zxdc3pf5+m6nmfhUYjMczPxL9EPGHUle9XgGQKO77P7S64e1L77/caL7sDG1Wnee3f64R19qShy/8w5UtkMIeawtz9l7zjqCmN4q7xudVQDAn7jwlk7Mdx24/JTgUDt98QibnL3+mj6n2t3Ir98faqNzvlFfusH3K/dE6o/v3kpjI/BvdYoKY0k75RHHixMHV1RUXFxfD2x9PnDhBSEgI48aNo0CBAqRLl47798P/gpg8eXLatGnDunXr6NatG7NnzzYcS5AgAU2bNmXJkiVMnDiRWbNmGY69fg7dnj17KFGiBObm5hQrVoyxY8fi7+9vmDGXJk0arKysOHDggOHcwMBAjh07RqZMmd6bKU2aNMSKFYsjR44Y9vn4+HDlyvsf4A7Qp08fnj59arT16NXnI3cwTCwrKzJmysyRw4cM+0JCQjhy5BDZsueM8JxsOXJw5PBho32HDx0kW44cACRNlgwnpwQcOfKmzhcvXnDu7JkI6/T392fU8KEMGDwUC4uwJZKv32gbFBhESEhwuHO+lKnmfterVy+5d/eO4R/xcG3088Pc3HgGibl52F+nr9/y5Ofni7mZ+TtlLAgNjXj51uTxo6nbsAkJEzkTEhxi9Pbi4OBggtXfUSo0JJTgwACCAsIGGt59LoWZuTmhIVH75Prn3p74vnhGHPv44Y4FBQTwz8IplG/eOez7JCSY4OCw+xAcHERoyJct+wPT7W9TzW1taU6iuNY8eRXxm9BTONgC8MQ38KN1+QaG8Nw/COe41qR2jM2JO0/DlSmZ1pETd57y3P/9b16Pa21JrWzOzD96FwBzszfPurMwN8M8Ch4PY6r9rdzKrdzK/TblfiOm5RbTpgE6E+Dq6kpgYCBTpkzh+vXrLF68mJkzZxqV6dy5M9u3b+fGjRucPHmS3bt3kzFjRgAGDhzIhg0buHr1KhcuXGDTpk2GYxD2HLqLFy9y4cIFihQpYti3dOlS8uTJY5gNFydOHNq2bUuPHj3Ytm0bFy9epFWrVrx69YoWLVq8t/12dna0aNGCHj16sGvXLs6fP0+zZs0MAyLvY21tzQ8//GC0RWZ5a+OmzVm3ZhUb1//J9WvXGD50ML6+vlSvUROAfn16MmnCm7fJNvqpCQcP7GPhgnncuH6NGdOmcOH8eeo3/AkIGwBo1LgJs/+YwZ5dO3G/4kb/Pj1JkDAhpUqXCXf9WTOnU6RYcTJmDBu8zJEzFzv/+ZsrbpdZsXwJOXLm+uQskWGKuadOGMupE8fwuH+Pc2dO0ad7JyzMLShToRIAwwb2YcaUCYbyhYuV4M81K/ln+xbu37vL0cMHmT1jCoWLlcDCwiKsTNESLJw3i4P7/sXj/j3+3fUPK5cupFjJ0uGuf/TwQe7cukmtug0AyJg5C7du3uDQgX1sWLcKc3NzUqT4/KWWH2IK/f3vyrncuXyWp54P8Lxzg39XzuX25TNkKlSa+ImTY58oCdvnT8Lj2mV8Ht7n6JbV3Dx/krS53zxAeMWoHpz8e73h6wA/Xx7eusrDW1cBeOL5gIe3rvLM65Hh+O7ls7h/9SJPPR9w68JJ1k0YhEOiJKTKGv55ggc3LCF19nwkSukKQNJ0WXA/vp9Ht69z8u8NJE2b+YvvA5hGf5tq7p/yJCFjIjsSxLEiXYI4dCuZipDQUA7c8CFRXCtqZktEqvi2JIhjRe7kP9C+aAouPnhueGkDwLjqGcnrEs/wdf4U9mRKZEdCOytyJ49Hv3JpOHbnKWfvPze6dqK4VmRIZMcud+MZCe9qmi8pmy8+wudV2KCg26OXFEkdnyTxrCmdzhG3Ry8/eP6nMoX+Vm7lVm7lVu7vN7eYri9+Bp18+7Jnz8748eMZPXo0ffr0oVixYowaNYomTZoYygQHB9O+fXvu3r3LDz/8QIUKFZgwIWxAwsrKij59+nDz5k1sbW0pWrQoK1asMJybNWtW7O3tSZcuneHNryVKlCA4ONjw/LnXfvvtN0JCQmjcuDHPnz8nT548bN++HQcHhw9mGDt2LC9evKBKlSrEjRuXbt268fRp+E/wo1KFipXw8fZm+tTJeHl5kj5DRqb/MQfH/6Y/P/DwMJohlSNnLkaN+Z2pkycyZeJ4XFKkZOKUaaRNm85QpnmLVvj6+jJ08ECeP39Gzly5mf7HnHADh+7uV9ixbSsr16437CtbrgLHjx6leZNGpEiZit/GjONrMMXcjx49ZFDfHjx7+gR7h/hky5GLPxYsw8EhbKbTwwceRjOsmrb4BTMzM2ZNn4yn5yMc7B0oXKwErdt3MpTp0rMfs2dM5vffhuHj442TU0Kq1apjeEbda/5+fowfM4Kho343DDonTORMlx59GTmkH7FiWdF/yEisbWyiPDeYRn+/evaEzX+M4eUTb6xt45DAJRV1e4wiZdbcANTuPoK9K+eydvwAAv38sE+UhB9b9yBNjjfPvXzyyINXb72B9cGNK6wY2d3w9e5lYR96ZClSlkq/9MTM3BzPO9e5sO9v/F69wM7BkZRZclO0djMsYxk/S9Dzzg0uH/mXZsPffHCSPm9Rbl86w7LhXYifODlV2n3a7N+PMYX+NtXc8WNb0bFYSuJaW/DMLwi3Ry8ZsOUKz/2DsLKIRZbEcamYMSHWscx5/DKAI7ee8OfZB0Z1JI1nQ+xYFoavHWxj0SRvUuLZWOLjG8S+a96sfeccgJKujni/DAw3cPe2bEni4hzXmmlvPY9u+2VPUjvFZnil9FzzesXaM+Hr/hym0N/KrdzKrdzK/f3mjuliyhtTv0Vmoa/XY31E165dP3jc09OTZcuWERysaZ7y7fJ7/8ob+Q69MNEOt7Mxzc9elp6M+JmB37tGuVyiuwnyf9Rs6anobkK0WNAo4uVMIiIiMYEp/Xj+6/rL0d2ECE2uniG6m/BRn/xtcurUx38gLFas2Bc1RkRERERERERExNR88gDd7t27v2Y7REREREREREQkBouKlz6ZKr0kQkREREREREREJBppgE5ERERERERERCQamdCjCkVERERERERE5GvREtfPpxl0IiIiIiIiIiIi0UgDdCIiIiIiIiIiItHoswbo9u3bx08//UTBggW5d+8eAIsXL2b//v1R2jgREREREREREYkZzMzMvsktJoj0AN3atWspX748tra2nDp1Cn9/fwCePn3KyJEjo7yBIiIiIiIiIiIi37NID9ANHz6cmTNnMnv2bGLFimXYX7hwYU6ePBmljRMREREREREREfneRfotrm5ubhQrVizc/njx4vHkyZOoaJOIiIiIiIiIiMQweovr54v0DDpnZ2euXr0abv/+/ftJnTp1lDRKRERERERERETEVER6gK5Vq1Z06tSJI0eOYGZmxv3791m6dCndu3enbdu2X6ONIiIiIiIiIiIi361IL3Ht3bs3ISEhlC5dmlevXlGsWDGsra3p3r07HTt2/BptFBERERERERGRb1wMeWHqNynSA3RmZmb069ePHj16cPXqVV68eEGmTJmws7P7Gu0TERERERERERH5rkV6gO41KysrMmXKFJVtERERERERERERMTmRHqArWbIkZh+Ys7hr164vapCIiIiIiIiIiMQ85lrj+tkiPUCXI0cOo68DAwM5ffo058+fp2nTplHVLhEREREREREREZMQ6QG6CRMmRLh/8ODBvHjx4osbJCIiIiIiIiIiYkrMo6qin376iXnz5kVVdSIiIiIiIiIiEoOYf6NbTPDZL4l416FDh7CxsYmq6kREvpidTZT9FScxQKNcLtHdBJGvbkGjnNHdhGjhkLdDdDchWvgcmxrdTRAREZH/k0j/9lqzZk2jr0NDQ/Hw8OD48eMMGDAgyhomIiIiIiIiIiJiCiI9QBcvXjyjr83NzUmfPj1Dhw6lXLlyUdYwERERERERERGJOfQS188XqQG64OBgmjdvTtasWXFwcPhabRIRERERERERETEZkXpWnoWFBeXKlePJkydfqTkiIiIiIiIiIiKmJdJLXLNkycL169dJlSrV12iPiIiIiIiIiIjEQOZa4/rZIv222eHDh9O9e3c2bdqEh4cHz549M9pERERERERERETk033yDLqhQ4fSrVs3KlWqBEDVqlUxe2tkNDQ0FDMzM4KDg6O+lSIiIiIiIiIiIt+pTx6gGzJkCG3atGH37t1fsz0iIiIiIiIiIhIDaYXr5/vkAbrQ0FAAihcv/tUaIyIiIiIiIiIiYmoi9Qw6Mw2FioiIiIiIiIiIRKlIvcU1Xbp0Hx2k8/b2/qIGiYiIiIiIiIhIzGOueV2fLVIDdEOGDCFevHhfqy0iIiIiIiIiIiImJ1IDdPXr1ydhwoRfqy0iIiIiIiIiIiIm55MH6PT8OREREREREREReR9zjR19tk9+ScTrt7iKiIiIiIiIiIhI1PnkGXQhISFfsx0iIiIiIiIiIiImKVLPoBMREREREREREYmIVrh+vk9e4ioiIiIiIiIiIiJRTwN0IiIiIiIiIiIi0UhLXOX/rlmzZjx58oT169dHd1NEREREREREJIqYa4nrZ9MMuijQrFkzzMzMMDMzw8rKCldXV4YOHUpQUNAX1Vm9evVInfPvv/9SqlQp4sePT+zYsUmbNi1NmzYlICDgs9vxNUyaNIkFCxZEdzM+yYplS6lYthR5c2alUf06nDt79oPld2zfSrXKFcibMyu1qldh395/jY6HhoYybcokShcvQr5c2Wjdohm3bt00HA8ICKBv7x4UypeLKpXKc/jQQaPzF8ybw6gRw6Is3/sot3J/iHIr99u+x9xXr7rTtVNHKpYtRfbM6VmyaEG4MqtWLKN2jSoUypeLQvly0bhhPfbvM743Y0ePomjBfJQrXZzNmzYaHduxfSsd27WJkmwfYgr9bRfbmrHda+G2ZSjeh8aze0FXcmdyMRxPGD8us4b8xPUdI3h8cDwbprYjjUuCj9bboWEJzvw5AO9D43HfOowx3WpibfXms+3Lm4fge2pquG1C77qGMqO71eTentG4bx1G/Yp5jOqvWSYnayb+EgV34A1T6O+IKLdyf4hyK/fbYkpuMU0aoIsiFSpUwMPDA3d3d7p168bgwYMZO3ZspOsJDg7+rDfmXrx4kQoVKpAnTx727t3LuXPnmDJlClZWVgQHB0e6vq8pXrx42NvbR3czPmrb1i38PmYUv7Rrz4rVf5I+fQba/tKCx48fR1j+9KmT9O7RjRo1a7NyzXpKlipN547tcXe/Yigzf+5sli9dTP9Bg1myfBW2tra0bd0Cf39/ANasXsmlCxdYtGwltevUpXfPboSGhgJw9+4d1q5ZTcdOXZRbuZVbuZX7K+b28/UlWfJk/NqlG05OEQ/kJEzkTKcu3Vm+eh3LVq0lX/4CdOrQnqtX3QHYs3sXWzdvYubsuXTp2oMhA/vj4+MNwPPnz5kyaSJ9+w/8OoH/Yyr9PWNgQ0oVyMDP/ReSp+5I/jl0mc0zO5IkQTwAVk1oTapkTtTp/AcFGvzGbQ9vtszsSGwbq/fWWa9CHob9Wo2Rf2wlR83htBmylNrlczO0Y1VDmSI/jSVlmT6GrVKbKQCs+/sUAJWKZaFuhTxUaTeNfpPWM31gQxzt4wDwg50NgztUoctvq6LsPphKfyu3ciu3cn/vucV0aYAuilhbW+Ps7EyKFClo27YtZcqUYePGjfj4+NCkSRMcHByIHTs2FStWxN3d3XDeggULsLe3Z+PGjWTKlAlra2t+/vlnFi5cyIYNGwwz8/bs2fPB6+/YsQNnZ2fGjBlDlixZSJMmDRUqVGD27NnY2toayh04cIASJUoQO3ZsHBwcKF++PD4+PgBs27aNIkWKYG9vj6OjI5UrV+batWuGc2/evImZmRnr1q2jZMmSxI4dm+zZs3Po0KFwebZv307GjBmxs7MzDF6+9u7swBIlSvDrr7/Ss2dP4sePj7OzM4MHDzbKd/nyZYoUKYKNjQ2ZMmXin3/+wczM7Ksuk128cD41a9eleo1apHF1pf+gIdjY2LB+3doIyy9dsohCRYrS7OeWpE6Thg6/diZjpkysWLYECPu0ZuniRbT6pS0lS5UhXfoMDB81Bs9Hj9i18x8Ably7RvGSpXB1TUu9Bo3w8fY29M+IoYPp3LU7dnZ2Xy2zciu3ciu3ckOWrNno2r0XFSv9iJVVxIM4JUqWomix4qRIkZKUKVPRsVMXYseOzdkzpwG4cf0aefLlI3OWrFT8sTJx7Oy4d/cuABPGjaVuvQYkTpLkq+R9zRT628Y6FtVL56DfxPUcOHmN63e8GPHHFq7d8aRVnaK4uiQkf7ZU/DpiBScu3sb91iN+HbkSG+tY1K2Y+731FsieikOnr7Ny23Fue3iz8/BlVm07Tp7MKQxlvHxe8PDxc8NWqWgWrt32ZN+JsJ/zMqRyZt8Jd05evM2qbSd49tKPlEkcw+5Fp+rMXr2POw98ouxemEJ/K7dyK7dym0LumM7sG/1fTKABuq/E1taWgIAAmjVrxvHjx9m4cSOHDh0iNDSUSpUqERgYaCj76tUrRo8ezZw5c7hw4QKTJ0+mbt26hoEtDw8PChUq9MHrOTs74+Hhwd69e99b5vTp05QuXZpMmTJx6NAh9u/fT5UqVQwz7F6+fEnXrl05fvw4O3fuxNzcnBo1aoSb0devXz+6d+/O6dOnSZcuHQ0aNDBazvvq1St+//13Fi9ezN69e7l9+zbdu3f/YPsXLlxInDhxOHLkCGPGjGHo0KH8/fffQNiswurVqxM7dmyOHDnCrFmz6Nev3wfr+1KBAQFcuniBAgXf3Hdzc3MKFCjE2TOnIjzn7OnTFChQ0GhfocJFOHv6NAD37t7Fy8uT/AXe1Bk3blyyZstuqDNdhgycOnkCPz8/Dh7YT4IECXBwcGDzpo1YW1tTukzZKE5qTLmVW7mV+22mmjuygoOD2bplM76+r8iePScA6dJn4OL58zx7+pSLF87j7+eHi0sKTp44zuWLF2j4U+Moufb7mEp/W1qYY2lpgV9AoNF+P/9ACuVMY1iS6hfw5ueU0NBQAgKCKJQjzXvrPXzmBjkzJTcMyKVM6kj5wpnZtv9ChOVjWVpQv1JeFm5486Hl2Sv3yJXRBfu4tuTMmBxb61hcu+NJoRypyZkxOdOW7/nc2OGYSn+/S7mVW7mV+23fQ24xbXpJRBQLDQ1l586dbN++nYoVK7J+/XoOHDhgGGBbunQpyZMnZ/369dSpUweAwMBApk+fTvbs2Q312Nra4u/vj7Oz8yddt06dOmzfvp3ixYvj7OxMgQIFKF26NE2aNOGHH34AYMyYMeTJk4fp06cbzsucObPhz7Vq1TKqc968eSRIkICLFy+SJUsWw/7u3bvz448/AjBkyBAyZ87M1atXyZAhgyHPzJkzSZMm7AffDh06MHTo0A+2P1u2bAwaNAiAtGnTMnXqVHbu3EnZsmX5+++/uXbtGnv27DHcjxEjRlC27If/cvT39zdMVX4t1MIaa2vrD54H4PPEh+DgYBwdHY32Ozo6cuPG9QjP8fLywtHRKVx5r8de/x33DNvnFL5OL6+wMtVr1MLdzY0aVSvhYO/AmHETefb0KdOnTmbu/MVMnTSBbVu3kCy5C0OGjyRRokQfzRIZyq3cr9uo3MaU+51M33nuT+V+xY3GDesTEOBP7NixmTB5GmlcXQEoXKQoP1apSsN6tbG2sWHYyNHY2toyYtgQho0YxaoVy1m+bDEO9g4MGDIMV9e0X9SWd5lKf7945c/hM9fp06oibjce8vDxM+pWyEP+bKm4dscTt5sPuO3hzbCOVekwfDkvfQP49aeSJHN2wNkp3nvrXbntOI4Ocdg5vwtmmBErlgWzVu9j7LwdEZavWjIb9nFtWfLXEcO+fw5dYvmWY+xf0hNf/0BaDVzMS98AJvWtT+tBi2ldpyht6xfn8ZMXtB+2nEvXH3z2fTCV/n6Xciv36zYqtzHlfidTDMotpk0DdFFk06ZN2NnZERgYSEhICA0bNqRmzZps2rSJ/PnzG8o5OjqSPn16Ll26ZNhnZWVFtmzZvuj6FhYWzJ8/n+HDh7Nr1y6OHDnCyJEjGT16NEePHiVx4sScPn3aMCgYEXd3dwYOHMiRI0fw8vIyzJy7ffu20QDd221NnDgxAI8ePTIM0MWOHdswOPe6zKNHjz7Y/nfzv32Om5sbyZMnNxqszJcv3wfrAxg1ahRDhgwx2tdvwCD6Dxz80XOjS6xYseg7YJDRvgH9+tCwUWMuX7rIrl07WbVuAwvmzWH0yOGMnzQlmloatZT7DeVWbuWOOblTpkzFqrXrefHiOX/v2M6Avr2Yu2CJYZCubfuOtG3f0VB+5vSpFChQEEtLS2b/MYM16/9i77+76d+nFytWr4uuGFEqOvr75/6L+GNwI67vGEFQUDCnL99h1bbj5MzoQlBQCPW7zWbGoEZ47B1LUFAwu464sW3/Bcw+sNqlaO609Pi5PJ1GreTYuVukSe7E7z1q49GqAr/N3haufNPqhdh+4CIenk+N9o/4Ywsj/thi+Lpv64rsPnKZwKBgerWsQN66I6lYNAtzhjWhcKMxX3wv/t++5/++P0S531Bu5Vbu7yN3VNJbXD+flrhGkZIlS3L69Gnc3d3x9fVl4cKFmH3oJ7+32NrafnLZj0maNCmNGzdm6tSpXLhwAT8/P2bOnGm4zodUqVIFb29vZs+ezZEjRzhyJOxT4HffAhsrVizDn1+3++1lsG8ff13m9YM13yeicz7nZRlv69OnD0+fPjXaevTq80nnOtg7YGFhEe4BpI8fP8bJySnCc5ycnHj836czRuX/+xTn9YPGH3t9ep1Hjxzm2lV36jf8iWPHjlK0aDFix45NuQoVOX7s6CdliQzlVu6PtVG53ymv3GH7vrPcnyqWlRUuKVKQKXMWOnXpRrr0GVi6ZFGEZW9cv8bmvzbSvmMnjh07Su48eYgfPz7lylfk0sULvHz54ova8i5T6u8bd70o13ISjgW7krbiAIo2/p1YlhbcuBeW5dSlOxSo/xuJinYnVbl+VOswHcd4cbhxN+KHjAMMavcjyzcfZcGfh7hw9T4bd59l4NS/6NG8XLif2VwSO1Aqf3oWrD/4ntrCpEuZiAY/5mXI9E0Uy5OWAyev4uXzgrU7TpIrkwt2sT8+w/99TKm/36bcyv2xNir3O+WVO2zfN5xbTJsG6KJInDhxcHV1xcXFBUvLsImJGTNmJCgoyDDQBWH/8bu5uZEpU6YP1hcVb191cHAgceLEvHz5EgibpbZz584Iy75uV//+/SldujQZM2Y0PAwzuqVPn547d+7w8OFDw75jx4599Dxra2t++OEHo+1TlrdC2C9dGTNl5sjhN8+SCQkJ4ciRQ2T77/lC78qWIwdHDh822nf40EGy5cgBQNJkyXBySsCRI2/qfPHiBefOnomwTn9/f0YNH8qAwUOxsLAgJCTY8Ky/oMAgQkKi/u28yq3cyq3cbzPV3J8rJCSEwHc+1IKwx18MGzKIbj17EztOHEKCQwh8nfu//w8O/rIPpd5liv39yi+AB17PsI9rS5lCGdm055zR8Wcv/PDyeUEalwTkyuTCpj1n31uXrY0VISHGHy6+/uDw3c9UG1ctyCPv52zdF/Hz6V6b2r8+vcat46VvABbm5sSytAAw/L+F+ef/WG6K/Q3KrdzKrdzGvofcYto0QPcVpU2blmrVqtGqVSv279/PmTNn+Omnn0iaNCnVqlX74LkpU6bk7NmzuLm54eXlZfRSiYj88ccftG3blh07dnDt2jUuXLhAr169uHDhAlWqVAHCZpQdO3aMdu3acfbsWS5fvsyMGTPw8vLCwcEBR0dHZs2axdWrV9m1axddu3aNsnvxJcqWLUuaNGlo2rQpZ8+e5cCBA/Tv3x8gymYeRqRx0+asW7OKjev/5Pq1awwfOhhfX1+q16gJQL8+PZk0YZyhfKOfmnDwwD4WLpjHjevXmDFtChfOn6d+w58MbW3UuAmz/5jBnl07cb/iRv8+PUmQMCGlSpcJd/1ZM6dTpFhxMmYMG8zNkTMXO//5mytul1mxfAk5cuZSbuVWbuVW7q+QOzAggMuXLnH50iUCAwN49Oghly9d4vatW4YykyaM48TxY9y7dxf3K25MmjCO48eOUqlylXDXX7dmNQ4O8SlRspQh97Ejhzl75jRLFi0gdRpXw/NiozN3TO3vMgUzUrZQRlIkcaRU/gxsm92JKzcesmhj2C9gNcvkpGjutKRM6kjlElnZPKMDf+05y87Dlw11zBnWmKEdqxq+3rL3PK3qFKFO+dyGege2rcyWveeMBu7MzMxoUq0ASzcd+eAga/MahfDyecGWvecBOHT6OsXzpiNf1pR0/KkkF6958PSF7xfdB1Ppb+VWbuVW7u89d0xnbvZtbjGBnkH3lc2fP59OnTpRuXJlAgICKFasGFu2bAm3pPNdrVq1Ys+ePeTJk4cXL16we/duSpQo8d7y+fLlY//+/bRp04b79+9jZ2dH5syZWb9+PcWLFwcgXbp07Nixg759+5IvXz5sbW3Jnz8/DRo0wNzcnBUrVvDrr7+SJUsW0qdPz+TJkz94zf8XCwsL1q9fT8uWLcmbNy+pU6dm7NixVKlSBRsbm6923QoVK+Hj7c30qZPx8vIkfYaMTP9jDo7/TX9+4OGBudmbMe4cOXMxaszvTJ08kSkTx+OSIiUTp0wjbdp0hjLNW7TC19eXoYMH8vz5M3Lmys30P+aEm9nn7n6FHdu2snLtesO+suUqcPzoUZo3aUSKlKn4bcw4vgblVm7lVm5Tz/3I8xH1alc3fL1w/jwWzp9Hnrz5mLtgMQDe3o/p36cXnp6PsIsbl3Tp0jNj1lwKFipsdO3HXl7MmTWThUuXG/ZlzZaNxk2b06HtL8R3jM+wEaO/idwxtb/j2dkwtGNVkiayx/vpKzbsPM2gaX8RFBQ2YOac4AdGd6tJQse4PPB6xtJNRxg1y/g5csmd4xsNvP02ZxuhoaEMaleZJAnj4eXzgs17zzN46l9G55XKnx6XxPFZuN54xsbbEsaPS6+W5SnZbLxh3/ELt5i0ZCfrJrfF0/s5rQYu/uL7YCr9rdzKrdzK/b3nFtNlFvqxh4OJfIMOHDhAkSJFuHr1qtELKT7GL+grNkpERES+Coe8HaK7CdHC59jU6G6CiIhEARsTmho1Zve16G5ChHqW/PRxg+hiQt8mEpP9+eef2NnZkTZtWq5evUqnTp0oXLhwpAbnREREREREROTr+ZqPofre6Rl0McTIkSOxs7OLcKtYsWJ0N++re/78Oe3btydDhgw0a9aMvHnzsmHDhuhuloiIiIiIiIjIF9MS1xjC29sbb2/vCI/Z2tqSNGnS/3OLYiYtcRUREYl5tMRVRERiMlNa4jp2z/XobkKEepRIHd1N+CgT+jaJ2eLHj0/8+PGjuxkiIiIiIiIiIhGKKW9M/RZpiauIiIiIiIiIiEg00gCdiIiIiIiIiIhINNISVxERERERERER+WJ6ievn0ww6ERERERERERGRaKQBOhERERERERERkWikJa4iIiIiIiIiIvLFzLXG9bNpBp2IiIiIiIiIiEg00gCdiIiIiIiIiIhINNISVxERERERERER+WLmWuH62TSDTkREREREREREJBppgE5ERERERERERCQaaYmriIiIiIiIiIh8Mb3E9fNpBp2IiIiIiIiIiMhbpk2bRsqUKbGxsSF//vwcPXr0k85bsWIFZmZmVK9ePVLX0wCdiIiIiIiIiIjIf1auXEnXrl0ZNGgQJ0+eJHv27JQvX55Hjx598LybN2/SvXt3ihYtGulraoBORERERERERES+mDlm3+QWWePHj6dVq1Y0b96cTJkyMXPmTGLHjs28efPee05wcDCNGjViyJAhpE6d+jPunYiIiIiIiIiIyHfK39+fZ8+eGW3+/v4Rlg0ICODEiROUKVPGsM/c3JwyZcpw6NCh915j6NChJEyYkBYtWnxWG/WSCBERkRgsJCQ0upsQLczN9QRiU+JzbGp0NyFaOFQcHd1NiBY+W3tFdxOixQu/oOhuQrSws9GvpCLy9Y0aNYohQ4YY7Rs0aBCDBw8OV9bLy4vg4GASJUpktD9RokRcvnw5wvr379/P3LlzOX369Ge3UX8bioiIiIiIiIjIF/tW3+Lap08funbtarTP2to6Sup+/vw5jRs3Zvbs2Tg5OX12PRqgExERERERERGR75a1tfUnD8g5OTlhYWHBw4cPjfY/fPgQZ2fncOWvXbvGzZs3qVKlimFfSEgIAJaWlri5uZEmTZqPXlfPoBMREREREREREQGsrKzInTs3O3fuNOwLCQlh586dFCxYMFz5DBkycO7cOU6fPm3YqlatSsmSJTl9+jTJkyf/pOtqBp2IiIiIiIiIiHyx7+UxwV27dqVp06bkyZOHfPnyMXHiRF6+fEnz5s0BaNKkCUmTJmXUqFHY2NiQJUsWo/Pt7e0Bwu3/EA3QiYiIiIiIiIiI/KdevXp4enoycOBAHjx4QI4cOdi2bZvhxRG3b9/G3DxqF6WahYaGmubr38QkmejLsUTkO6a3uIp8v/QWV9Oit7iKfL9M6dt85qGb0d2ECLUpmDK6m/BRJvRtIiIiIiIiIiIiX4v5t/oa1xhAL4kQERERERERERGJRhqgExERERERERERiUZa4ioiIiIiIiIiIl9MK1w/n2bQiYiIiIiIiIiIRCMN0ImIiIiIiIiIiEQjLXEVEREREREREZEvpre4fj7NoBMREREREREREYlGGqATERERERERERGJRlriKiIiIiIiIiIiX0wrXD+fZtCJiIiIiIiIiIhEIw3QiYiIiIiIiIiIRKMYPUA3ePBgcuTIEd3NMDAzM2P9+vXvPX7z5k3MzMw4ffo0AHv27MHMzIwnT54AsGDBAuzt7b96O0VEREREREREopr5N7rFBNHWzipVqlChQoUIj+3btw8zMzPOnj37f27V15U8eXI8PDzIkiVLhMfr1avHlStXDF9/awOQpmjFsqVULFuKvDmz0qh+Hc595Htyx/atVKtcgbw5s1KrehX27f3X6HhoaCjTpkyidPEi5MuVjdYtmnHr1k3D8YCAAPr27kGhfLmoUqk8hw8dNDp/wbw5jBoxLMryvY9yK/eHKHfEuf/5ewe/tPqZYoXykz1zei5fuhSujrGjR1G0YD7KlS7O5k0bw9XfsV2bLw/2ASeOH6NThzaULVWUnFkzsHvnP5987ulTJ8mTIzP1alc32h8cHMy0KZP4sUJpCuTJTpWKZZk1czqhoaGGMosWzKVU8UKUKl6IRQvnGZ1/7uwZGtatSVBQ0Bdl+xh9nyv3h8TE3Ha2VoxtWxq3JW3w3tSV3RN/Inc6ZwAsLcwZ3rI4x2b9jNfGLlxf0Y45PX8ksaPdB+vsXr8A+6c24dGGztxa1YFVg2uQNll8ozKpEtuzclANbq/uyMP1nVnSvxoJ7WMbjlvFsmBurx95uL4zZ+e3omTOFEbnd6mTj/Hty0TRXQhjCv39Ls9HDxnSvxcVSxWiZKFcNK5bnUsXz7+3/J5df9OpXUt+LF2EssXy0bpZQ44c3G9U5s/VK2hSrwZli+UzlDl0YJ9RmcnjR1OhZEFqVCrN9i2bjI7t+ns7PTu3i7qQ72GK/Q3KbWq5xTRF2wBdixYt+Pvvv7l79264Y/PnzydPnjxky5YtGlpmLDg4mJCQkCipy8LCAmdnZywtI343h62tLQkTJoySa5mSqOyjt23buoXfx4zil3btWbH6T9Knz0DbX1rw+PHjCMufPnWS3j26UaNmbVauWU/JUqXp3LE97u5vBl3nz53N8qWL6T9oMEuWr8LW1pa2rVvg7+8PwJrVK7l04QKLlq2kdp269O7ZzfBL7t27d1i7ZjUdO3WJ8qzKrdzK/eW5fX1fkTNnLjp37R5hHXt272Lr5k3MnD2XLl17MGRgf3x8vAF4/vw5UyZNpG//gVEf9i2+vr6kS5eBPv0id53nz54xoG8v8uUvEO7YgnmzWbNqOb37DmDdhs382qUbC+fPYfmyxQBccXNjxrQp/DZmPKNGj2P6lEm4X3EDICgoiBHDBtNv4JD3/tsYFfR9rtzfY+4ZXStQKldKfh69iTyt5/HPiRtsHlOfJI52xLa2JIerM78tOUjBdgupP2Q96ZLFZ/XQmh+ss2i25MzceJLivy6hcu+VWFpasOm3usS2iQVAbJtYbPqtLqGEUrHHckp1XoKVpTlrh9UyPBS8RaXs5EzrTIlOS5i3+QwL+lQx1J/COR7NK2Vn0Py9UXYfTKW/3/bs2VPa/PwTlpaWjJs8k6WrN9KhSw/ixv3hveecPnmcfPkL8vvkGcxbsppcefLRs0t7rlx+82FSgkSJaNOxC/OWrGbu4lXkzpuf3l07cP3aVQD2793N39s2M2HabNr92pXfhg/kiY8PAC+eP2fW9El07dX/q+UG0+xv5Ta93GK6om2ArnLlyiRIkIAFCxYY7X/x4gWrV6+mRYsW4ZZ7rl+/HrMPvBKkWbNmVK9end9//53EiRPj6OhI+/btCQwMNJTx9/ene/fuJE2alDhx4pA/f3727NljOP56menGjRvJlCkT1tbW3L59m2PHjlG2bFmcnJyIFy8exYsX5+TJk+Ha4OHhQcWKFbG1tSV16tSsWbPGcOzdJa7venuJ64IFCxgyZAhnzpzBzMwMMzMzFixYwM8//0zlypWNzgsMDCRhwoTMnTv3vffmtTVr1pA1a1ZsbW1xdHSkTJkyvHz50nB83rx5ZM6cGWtraxInTkyHDh0Mx8aPH0/WrFmJEycOyZMnp127drx48SJc+7dv307GjBmxs7OjQoUKeHh4GMp8zT6KaosXzqdm7bpUr1GLNK6u9B80BBsbG9avWxth+aVLFlGoSFGa/dyS1GnS0OHXzmTMlIkVy5YAYZ/WLF28iFa/tKVkqTKkS5+B4aPG4PnoEbv+m8Vy49o1ipcshatrWuo1aISPtzc+//3gM2LoYDp37Y6d3Yc//VZu5Vbu/39ugCpVq9OmXQfyFywYYR03rl8jT758ZM6SlYo/ViaOnR33/vuQasK4sdSt14DESZJEfdi3FClajPa/dqZU6bKROm/4sMFUqFSZbNlzhDt25vQpipcsTdFiJUiSNBlly1WgQKHCXDh3DoCbN66TNl168uUvQP4CBUmbLj03b9wAYOGCueTKnYfMWbJ+cbYP0fe5cn9vuW2sLKleND39Zu/mwLm7XL//hBGLD3Dtng+tquTk2asAKvdeydq9l3G/683RS/fpMvVvcqdLTPIEcd9bb7W+q1my4zyXbnlx7ronrcduxiVRPHKmTQRAwcxJSZEoHq3GbuHCTS8u3PSi5ZjN5EqXmBI5wmbKpXdxZPOhq1y65cXMjSdJ6BAHp3i2AEz+tRz95+zh+auAKLsXptDf4TIsmEvCRM70GzyCTFmykSRpMvIXLEyy5C7vPadz9z40atqCjJmzktwlBW06dCaZSwr2791tKFOkWEkKFSlGcpcUuKRIyS/tO2EbOzYXzp0B4NaN6+TMnY+MmbJQtsKPxIljh8f9sH/Hpk8eR/Xa9XBO/HX/HTPF/lZu08sd070ev/jWtpgg2gboLC0tadKkCQsWLDBaBrN69WqCg4MNI9iRtXv3bq5du8bu3btZuHAhCxYsMBoE7NChA4cOHWLFihWcPXuWOnXqUKFCBdzd3Q1lXr16xejRo5kzZw4XLlwgYcKEPH/+nKZNm7J//34OHz5M2rRpqVSpEs+fPze6/oABA6hVqxZnzpyhUaNG1K9fn0sRLHP6mHr16tGtWzcyZ86Mh4cHHh4e1KtXj5YtW7Jt2zajQa9Nmzbx6tUr6tWr98E6PTw8aNCgAT///DOXLl1iz5491KxZ03D/Z8yYQfv27WndujXnzp1j48aNuLq6Gs43Nzdn8uTJXLhwgYULF7Jr1y569uxpdI1Xr17x+++/s3jxYvbu3cvt27fp3t14NsnX6qOoFBgQwKWLFyhQsJBR/gIFCnH2zKkIzzl7+jQFChj/Yl6ocBHO/jcge+/uXby8PMlf4E2dcePGJWu27IY602XIwKmTJ/Dz8+Pggf0kSJAABwcHNm/aiLW1NaXLRO6X6shSbuVW7s/L/SnSpc/AxfPnefb0KRcvnMffzw8XlxScPHGcyxcv0PCnxp+V52vb8Oda7t29wy9t20d4PHuOnBw9cohbN8MG3dzcLnP65EkKFykGgGu6dNy6eRMPj/vcv3+PWzdvkiZtWu7cuc3G9eto37HTV22/vs+V+3vMbWlhjqWFOX6BwUb7/QKCKJQlWYTn/BDHmpCQUJ68/PSfsX+IYw2Az3M/AKxjWRAK+L91Xb/AYEJCQw3XPXf9EYWyJMPGypKyeVLh8fg5Xk99qV8qE/4BQWw84B7uOp/LVPr7Xfv37iZDpsz079mFH8sUpVnDWmxctzpSdYSEhOD78iU/xIsX4fHg4GD+2b4FP19fsmTLDoBr2vRcvnieZ8+ecvnSBfz9/Uia3IUzp07gdvkider/9MXZPsRU+1u5TSu3mLavt57kE/z888+MHTuWf//9lxIlSgBhy1tr1apFvPf8Y/ExDg4OTJ06FQsLCzJkyMCPP/7Izp07adWqFbdv32b+/Pncvn2bJP/NUujevTvbtm1j/vz5jBw5EgibkTZ9+nSyZ89uqLdUqVJG15k1axb29vb8+++/RjPa6tSpQ8uWLQEYNmwYf//9N1OmTGH69OmRymFra4udnR2WlpY4Ozsb9hcqVIj06dOzePFiw+DY/PnzqVOnzkdH8j08PAgKCqJmzZqkSBH2KWfWrG9mLQwfPpxu3brRqdObX5by5s1r+HPnzp0Nf06ZMiXDhw+nTZs2RtkCAwOZOXMmadKkAcIG24YOHWrUjq/VR+/y9/cPN9AbamGNtbX1B+8TgM8TH4KDg3F0dDTa7+joyI0b1yM8x8vLC0dHp3DlvR57/XfcM2yfU/g6vbzCylSvUQt3NzdqVK2Eg70DY8ZN5NnTp0yfOpm58xczddIEtm3dQrLkLgwZPpJEiRJ9NEtkKLdyv26jchv7WO5PUbhIUX6sUpWG9WpjbWPDsJGjsbW1ZcSwIQwbMYpVK5azfNliHOwdGDBkGK6uaSMfLordunWTyRPHM2/hkvcuQW3eojUvXrykRtVKWFhYEBwcTPtfO1OpctiyttSp09ChUxfatv4ZgI6du5I6dRp+admczl16cPDAfv6YMQ1LS0t69OpL7jx5I7zO59L3uXK/buP3lPuFbwCHL9yjT6NCuN1+zEOfl9QtmZH8GZNw7b5PuPLWsSwY3rIEq3Zf/OTZa2ZmMLZtaQ6ev8vFm2E5j166wwdI2gAA7tRJREFUz0u/QEa0LMHAef9iZmbG8BbFsbQwxzl+2M+hC7edI0vqhJya04LHz3z5adgGHOLaMKBpEcp3X86gZkWpUyIj1z2e0Ob3Ldx//OJDzfggU+nvd92/d5f1a1ZSr1FTmvzcmksXzzHh91FYxopFpSrVP6mO5Yvn88r3FaXLGj8T/Jr7FX5p3pCAgABsbWMz8vfJpEod9oF9/kJFKF+pCi0b18Pa2ob+g0dia2vL76OG0W/ICP5cs4I1K5dhb29Pz35DSJ3GNaJLfzZT7W/lNq3cYtqidYAuQ4YMFCpUiHnz5lGiRAmuXr3Kvn37GDp0KDdv3vysOjNnzoyFhYXh68SJE3Puv2U2586dIzg4mHTp0hmd4+/vb/QfvpWVVbjn3z18+JD+/fuzZ88eHj16RHBwMK9evQq3tLLgO0ubChYs+N4lrZ+rZcuWzJo1i549e/Lw4UO2bt3Krl27Pnpe9uzZKV26NFmzZqV8+fKUK1eO2rVr4+DgwKNHj7h//z6lS5d+7/n//PMPo0aN4vLlyzx79oygoCD8/Px49eoVsWOHPRw4duzYhsE5CLv/jx49Mqrna/XRu0aNGsWQIUOM9vX7H3t3HRZV1oAB/B2GFkRKsACVEFAEbKy1u7trdddgdS1EQcTCTmxU7O527QY7QZCyQAEJkYb7/YEOjoAi4DfqvL997vN9c++55553DhJnzrnX1Q0uU6d99TxZUlJSwmRXN6l9rlOc0btPP/j7PcG5c2exe/8heG/wwtzZM7Fo6XIZtbRoMXc25v59cwPA8JGOGD7SUfJ69UpP1K5dB4qKili3ZhX2HjyCSxfPw8XZCTv37JdhS7NmT0x2Go+/RzrC2KR8nuVOnzqBE8eOYPbcBahY0RRPn/pjwdzZ0NcvifYdOgEAunXviW7de0rOOXzoAIoVKwabqrbo2L4Vtu7Yg7dvIjBp4lgcO3kWysrKPzzfjyavX+fMne1H5x489yjWjG+F4J0jkZ6RiXuBEdh93g925oZS5RTFCtjq2gEiEfDPstP5rn+JY3NYm+ijyb/bJPui4pLQZ8ZBLPunOUZ0rIZMQcDu809wJyACmR9XZKRnZOLf5f/h8zs0rRnfGisP3kZVUwO0czBDzb83Ymz3Wlg4sil6TT9YmLdBJmT9dZ6ZmYlKVpXx96gxAADzSpYIfvYMB/ftztcA3ekTR7Fh7SrMWbQc2jrSAxVGJibw3rEPCQkJOH/mNGa5TYbnOm/JIN2Qv0ZiyF/ZM6o3rF2J6rVqQ1FREZvWr8HmXQdx7fJFzJzqjA3bvm9W389K1v0tK8ydTR5yF6VfYzHpz0nmT5sdMmQI9u3bh/fv32Pjxo2oWLEiGjZsCAUFBamlrwCk7lOWFyUlJanXIpFI8gCBhIQEiMVi3L59G/fu3ZNsfn5+WLp0qeQcNTW1HGuUBwwYgHv37mHp0qW4du0a7t27B11dXaSmFt09NPKrf//+CA4OxvXr17F161aUL18e9evX/+Z5YrEY//33H06cOAErKyssX74cFhYWCAkJgZqa2lfPDQ0NRdu2bWFjY4N9+/bh9u3bWLFiBQBIvQe5vf9f9uOP6qMvOTs7Iy4uTmqb4OT81XM+0S6hDbFYnOMGpNHR0dDT08v1HD09PUR/MZsmOjoaeh8/xdHT08/aF5X/On19biDoWSB69u6Lmzd9Ub9+A6irq6N5y1a4ddM3X1m+B3Mz97fayNxflNfNvXx+hAQH4diRwxjpOBo3b/qiWvXq0NHRQfMWreD35DE+fCj4rJKikPjhA548foS5s2eguq01qttaY+3qlQh46o/qttbw9bkBAFiycD4GDRmKlq3awMzcAm3bdUCffgOx0WttrvXGxMRg7aoVcHJ2wcOHD2BsbAJjYxPUqFkb6enpkqWyRYVf58z9rTb+qrlDwmPRfNwO6LZbBLPeK1HfcQuUFBUQEh4rKaMoVsA2lw4wKqmFtk678j17bvGopmhdqyJaTNiBV1HSt3M5ezsU1gPWwqjbcpTtsgxD5h5DaT0NhH523c81qGoEK2NdrDp0Bw1sjHDKNxiJyWnYd9Ef9avmfc+0/JCn/v6crp4+TMpXlNpnUr4C3kSE53FGtjOnjmPODDfMmLMQNWrlvGeqkpIyypYzRiVLawx3/Bem5hbYs2NrLjVl3ZPu1PEjGDrcEXdv3YStXXVoa+ugcbMWeOr/ROo+10VBXvubueUrN8k3mQ/Qde/eHQoKCti+fTs2b96MwYMHQyQSQV9fH+/fv5f6xl7YmWh2dnbIyMjA27dvYWpqKrV9vow0N1evXsU///yD1q1bSx6i8Gka7Odu3LiR47WlpWWB2qusrIyMjIwc+3V1ddGxY0ds3LgR3t7eGDRoUL7rFIlEqFu3Ltzd3XH37l0oKyvjwIED0NTUhImJCc6ePZvrebdv30ZmZiYWLlyI2rVrw9zcHK9fvy5Qrq8pTB99SUVFBcWLF5fa8rO8FQCUlJVhaWUNnxvXJfsyMzPh43MdNlXtcj3HxtYWPl/2//VrsLG1BQCUKVsWenr68PHJrjMhIQEPH9zPtc6UlBR4zJwO12nTIRaLkZmZgfT0dABAelo6MjNzfm0UFnMzN3MXLPf3EgQBM9zdMG7iJKgXK4bMjEykfcr98X8zMor+6dTfo5iGBvbsP4ydew5Itq7de8LEpDx27jmAKlWyZjEnJydBpCD964SCWAGZQu7tXzjPA336DYCBoaFUfwNARnrRP5WbX+fM/bvnTkxOQ8S7DyihoYKm1cvj6LWse7x9GpyrWEYbbZx24t3H+8h9y+JRTdG+rjlaTtyJsIi4PMtFxych7kMKGtoaoWSJYjh6/VmOMipKYixxbIZRS04hM1OAWCyCkmLW9wslRQWIFQo3z0Ie+xsAbKra4XmY9IcZz5+HfvMBDf+dPIZZ7i5wnz0fDvUb5utamZmZuU5IEAQB82a7w3HsRKirF0PG57k//m9RZ5fX/mZu+cpN8k3mA3QaGhro0aMHnJ2dER4ejoEDBwIAatWqBXV1dUyePBlBQUHYvn17jie+fi9zc3P06dMH/fv3x/79+xESEgJfX194eHjg2LFjXz3XzMwMW7ZsgZ+fH3x8fNCnT59cZ53t2bMHGzZsQEBAANzc3ODr6yv1JNTvYWJigpCQENy7dw9RUVFS91P7888/sWnTJvj5+WHAgAH5qs/HxwezZ8/GrVu38Pz5c+zfvx+RkZGSAcRp06Zh4cKFWLZsGQIDA3Hnzh0sX541ZdfU1BRpaWlYvnw5goODsWXLFqxevbpAub6mMH1U1PoNGIT9e3fj8MEDCA4Kwszp05CUlISOnToDAKY4T8TSxQsl5fv07Y9rVy9jk/cGhAQHYdWK5Xj86BF69s66Ya5IJEKffv2xbs0qXDh3FoEBT+HiPBH6JUuicZOmOa6/dvVK1GvQEJaWVgAAWzt7nD3zHwKe+mPnjq2wtbNnbuZm7p8kNwDExcbC388PwUFBAIDQ0BD4+/khKjIyx/X3790DbW0d/NGosST3TZ8beHD/HrZu9kaFiqYoXrx4kedOTPyAp/5+eOqf9fCiV69e4qm/H8LDsz5wWbZkIVwmOwHIuhGzqZm51KajowNlFRWYmplD7eOtDRo0bIT1a1fj8qULeP3qJc6d/Q9bN3ujceOcN1G+ce0qwsJC0aNXHwCAtXUVhIYE48rlS9i3ZxfEYoWvLqctKH6dM/fvmLtp9fJoVr08jA210NjeBCcX9ELAi3fYfOohFMUK2D61I+zNDTFozhGIFRRgoF0MBtrFJANkAHB8Xg/83SG7PUscm6FnE2sM8DiChMRUyTmqytl3xenXogpqWpZG+VIl0LOJFba5dsTy/TcR+PJdjjY693XAKd9g3A/Kut3J9Uev0KGeOSqX18ffHexx/fGrQr8P8tLfn+vRpz8eP3yATRvW4uWLMJw+cRSH9+9F5269JGVWLV+MGVOzV46cPnEUM6ZOhuOYCbCqXAXRUZGIjopEwmcPvFu1fDHu3bmF8NevEBQYgFXLF+Pu7Zto3qotvnTkwF6U0NZGvQaNAGQNGt6+6YNHD+9j17bNMKlQEZqaRf9zTB77m7nlL/evTkEk+im3X4FM70H3yZAhQ7B+/Xq0bt1a8mAAHR0dbN26FRMmTMC6devQpEkTTJs2DcOGDSvUtTZu3Ch5GMKrV6+gp6eH2rVrSz3oITfr16/HsGHDYG9vj3LlymH27Nk5nk4KAO7u7ti5cydGjBiBUqVKYceOHbCysipQW7t06YL9+/ejUaNGiI2NxcaNGyUDmE2bNkWpUqVgbW0tec++pXjx4rh06RKWLFmC+Ph4GBsbY+HChWjVqhWArGW8ycnJWLx4McaPHw89PT107doVQNb96xYtWoS5c+fC2dkZDRo0gIeHB/r371+gbF9T0D4qai1btUbMu3dY6bkMUVGRsKhkiZVrvKD7cfpzRHg4FETZv+Ta2tnDY94CeC5bguVLFsHI2ARLlq+AmVn2/fQGDRmKpKQkTJ82Fe/fx8POvhpWrvHKMbMvMDAAp0+ewK59ByX7mjVviVu+vhjUvw+MTcpjzryF+BGYm7mZu2C5L5w/h6ku2X8MOY3PugPT3yNGSd13LjoqCl5rV2PTth2SfVVsbNBvwCCMGv4XdHR1MGPW3B+S+8njRxg6OPtDnYXz5wAA2rXviOmz5iAqMhIR4d83O9ppsgtWei7D7JnTEfMuGvr6JdG1aw8MGz5CqlxycjLmeMzA3PmLofBxxp2BoSEmOrtgmutkKCkrY/qsOVBVVS1kypz4dc7cv2NuLXUVTB/SAGX0NPHufTIOXXkKtw2XkJ6RCSOD4mjnkPWgGd81g6XOaz5uOy4/eAEAqFBKG7rFsz9w/qt91h+b/y3sLXXO0PnHsPX0IwCAeVkdTB/cADqaagh7E4d5269j2b6bOdpnZaKHLg0rodbf3pJ9+y/7o37VcjizuA8CX0RjgMeRQr8P8tLfn7O0rgKPBUux2nMJvNetQqnSZTF6nBNatM7+XTk6KlJqyevhA3uRkZGOhXNnYuHcmZL9rdp2gIt71kPYYmPeYcZUZ0RHRaKYhiZMzcyxyHMtan72xEsAeBcdhU0b1mL1xuz7E1pVtkHPvgMwYfRwaGvrwsV9VpHnBuSzv5lb/nKT/BIJX94gjH4JCQkJKFOmDDZu3IjOnTvLujm/jOT0b5chIvqVZGbK549xhUIujSP6FWi3+jGD9T+7mBNOsm6CTCTI6S+qGqo/xZwRoh9Knr7Mt95+Kesm5KpvtbKybsI3ydGXye8hMzMTUVFRWLhwIUqUKIH27dvLuklERERERERERHyKayFwgO4X8/z5c5QvXx5ly5aFt7c3FBUVpY59bTntkydPYGRUuKdlERERERERERFR0eIA3S/GxMQEea1KLl269FefdJvfe9UREREREREREdH/DwfofiOKioowNTWVdTOIiIiIiIiISA79Ig9M/SkpfLsIERERERERERER/SgcoCMiIiIiIiIiIpIhLnElIiIiIiIiIqJCE3GNa4FxBh0REREREREREZEMcYCOiIiIiIiIiIhIhrjElYiIiIiIiIiICo2zwAqO7x0REREREREREZEMcYCOiIiIiIiIiIhIhrjElYiIiIiIiIiICo1PcS04zqAjIiIiIiIiIiKSIQ7QERERERERERERyRCXuBIRERERERERUaFxgWvBcQYdERERERERERGRDHGAjoiIiIiIiIiISIa4xJWIiIiIiIiIiAqNT3EtOM6gIyIiIiIiIiIikiHOoCMi+s0kp2XIugkyoaoklnUTZEJBQT4/pUxJy5R1E2RCRYmfrcqTmBNOsm6CTGi3mivrJsiEvPY3ERFl4QAdEREREREREREVGj9KLDi+d0RERERERERERDLEAToiIiIiIiIiIiIZ4hJXIiIiIiIiIiIqND7FteA4g46IiIiIiIiIiEiGOEBHREREREREREQkQ1ziSkREREREREREhcYFrgXHGXREREREREREREQyxAE6IiIiIiIiIiIiGeISVyIiIiIiIiIiKjQ+xLXgOIOOiIiIiIiIiIhIhjhAR0REREREREREJENc4kpERERERERERIWmwOe4Fhhn0BEREREREREREckQB+iIiIiIiIiIiIhkiEtciYiIiIiIiIio0PgU14LjDDoiIiIiIiIiIiIZ4gAdERERERERERGRDHGAjvLNxMQES5Ys+a5z/vjjD4wZM+aHtIeIiIiIiIiIfh6in/S/XwEH6H4TAwcOhEgkkmy6urpo2bIlHjx4IOum/dJ2bt+GVs0ao4ZdFfTp2Q0Pv/F+nj51Ah3atkQNuyro0rEdLl+6KHVcEASsWL4UTRrWQ017GwwbMhBhYaGS46mpqZg8aQIcatqjXesWuHH9mtT53hu84DFrRpHlywtzy1fuTzZtWIdatlZYNM8jzzLBzwLhNG40OrZqilq2VtixdXOu5d6+eQO3yRPRrGEdNKhlh95dO8Dv8SPJ8a2bNqBlo3po2agetm3eKHXuo4f30b9XV6SnpxdNsDzIa3/LY+69u3egd7cOaFS3OhrVrY7B/Xvi2pVLeZY/eugAatpaSm31alaVKpOY+AHzPWagbfM/UL+WLXp0bot9e3ZKlVm8YA6aNqiNti0a4eSxI1LHzpw+ibH/DC+6kHmQx/4GmPt3zq2hpoz5w5vg6da/8e7oWJxf0hfVzA0BAIpiBcz8syFurh2MqMP/InjnCHhNbINSuhpfrXN8z9q44tkfbw+NQdjuUdg9rRPMyurkKFfLsjROzOuJqMP/4s3BMfhvYW+oKmfd0ltZSYz1Tm3w5uAYPNg4FI3sjKXO/bdbTSwa2bSI3oUs8tDfuWFu5v6a3yU3yScO0P1GWrZsifDwcISHh+Ps2bNQVFRE27ZtZd2sHy41NfWH1HvyxHEsmOeBv0aMxM49B2BhUQnD/xqC6OjoXMvfu3sHkyaMQ6fOXbFr70E0atwEYxxHIjAwQFJm4/p12LFtC1zcpmHrjt1QU1PD8GFDkJKSAgDYu2cX/B4/xubtu9C1W3dMmjgOgiAAAF6+fIF9e/fAcfS/PyQvc8tn7k+ePHqIA3t3w9Tc4qvlkpOTUaZMWYwYPRa6enq5lomPj8OwgX0gVlTEEs812Ln/CP4ZOxGaxYsDAAIDnmLtKk/MnLsAM+bMx5oVy/Ds4/uWnp6OuTPdMWmKGxQVf9xzjOS1v+U1t4GBIUb+Mxabtu+F9/Y9qF6jNsaPGYWgZ4F5nlNMQwPHz1ySbIdOnJU6vmTBXFy/dgXus+Zh1/5j6Nm7PxbMmYlLF84BAC5fPI9TJ45h2SovOI4Zj1nTXREbEwMASHj/Hqs8l2Cis+uPCw357W/m/r1zrxrbEo3tTTB47lFUH7YBZ26H4Ni8niitqwF1FUXYmhpiztZrqDNiE3q6H4R5WR3smd75q3XWtymH1YfvoOE/W9F20i4oKopxdE53qKsqScrUsiyNQx7dcfZ2COo7bkG9UZux+tAdZH7MO6R1VdiZGeKP0Vux4dh9eDu3k5xrbKiFQa2rwm1j3h8MfC956W/mZm55zE3yiwN0vxEVFRUYGhrC0NAQtra2mDRpEl68eIHIyEgAgJOTE8zNzaGuro4KFSrA1dUVaWlpUnUcOXIENWrUgKqqKvT09NCpU6c8r+fl5YUSJUrg7NmsP1o+fPiA/v37Q0NDA6VKlcLChQtznBMTE4P+/ftDW1sb6urqaNWqFQIDpf9A2rdvH6ytraGiogITE5Mc9ZiYmGDGjBno378/ihcvjmHDhhXo/fqWLZs2onPX7ujYqQsqmprCxc0dqqqqOLh/X67lt23dDId69TFw8J+oULEiRv0zBpZWVti5fSuArE9rtm3ZjKF/DUejxk1hblEJMz3mIfLtW5w7ewYAEBIUhIaNGsPU1Aw9evVBzLt3iPn4B92s6dMwZux4aGh8/VNg5mbu75WY+AFTJ0/E5KnuKK5Z/KtlrSpXwT9jJ6B5y9ZQVlLOtcyWjetR0tAQU6fPhnUVG5QuUxa1HeqibDkjAEBYSDBMzcxRvWZt1KhVB6Zm5ggLCQaQNbPO1r46rCpXKdqQX7ZRTvtbXnPXb9gIdes3hJGxCYyNy2OE4xioq6vj0cP7eZ4jggh6evqSTVdXekD6wf27aNOuA6rVqInSZcqgU9fuMDO3wONHWZ/shwQHoVr1GrCyrowWrdqgWDENvH71EgCwfMkCdOnWE4alSv+40JDf/mbu3ze3qrIiOta3wJR153H14UsEv47FrC1XEfQqBkPb2SE+MRVtJ+3Cvkv+CHz5Dr5+r/Gv53+oZl4K5fQ186y3w+Q92Hr6EfzCovAwOBLD5h+DkYEW7MwMJGXmDW+ClQduY8EuH/iFRSHw5Tvsu+SP1LQMAICFkS6OXX8Gv7AorD58ByW1i0FPSw0AsOyf5nDxuoD3iUX3obI89DdzM7e85v7ViUQ/5/Yr4ADdbyohIQFbt26FqakpdHV1AQCamprw9vbGkydPsHTpUqxbtw6LFy+WnHPs2DF06tQJrVu3xt27d3H27FnUrFkz1/rnzZuHSZMm4fTp02jSpAkAYMKECbh48SIOHTqE06dP48KFC7hz547UeQMHDsStW7dw+PBhXL9+HYIgoHXr1pKBwtu3b6N79+7o2bMnHj58iGnTpsHV1RXe3t5S9SxYsABVq1bF3bt34epa9DMQ0lJT4ffkMWrXcZDsU1BQQO3aDnhw/26u5zy4dw+1a9eR2udQtx4e3LsHAHj18iWioiJRq3Z2nZqamqhiU1VSp3mlSrh75zaSk5Nx7eoV6OvrQ1tbG8eOHoaKigqaNG1WxEmlMbd85f5k/uyZqFu/IWp+1tbCuHTxHCytKsN5/Bi0bFQP/Xp0xsF9eyTHK5qZ40VYKCLCXyP89Ss8DwtDBVMzvHzxHEcPHcDfo0YXSTvyIq/9La+5v5SRkYHTJ48hKSkRVWxs8yyXlJSI9q0ao22LRhg/ZmSO2XY2Ve1w6cJ5vH3zBoIg4NZNHzwPC0WtOnUBAGYWleD35DHi4+Pg9+QxUlKSUdbICPfu3oa/3xP06N3vR8aU2/5m7t87t6JYAYpiBSR/HBT7JDk1HQ6Vy+Z6TvFiKsjMFBD7ISXf1yleTAUAEPM+GQCgX0IdNS1LIzL2A84v6YvQ3aNwemEvOFiXkZzzMPgtHCqXhaqyIppVL4/w6PeIiktCz8ZWSElNx+Grec/Y/V7y0t9fYm7mlofcJN9+3Poh+r87evSoZDT/w4cPKFWqFI4ePQoFhaxxWBcXF0lZExMTjB8/Hjt37sTEiRMBALNmzULPnj3h7u4uKVe1qvQ9d4CsmXhbtmzBxYsXYW1tDSBrQHD9+vXYunWrZMBu06ZNKFs2+5elwMBAHD58GFevXoWDQ9Y3xW3btqFcuXI4ePAgunXrhkWLFqFJkyaSQTdzc3M8efIE8+fPx8CBAyV1NW7cGOPGjSv0e5aXmNgYZGRkSAY3P9HV1UXIx5k+X4qKisoxw0JXVxdR0VEfj2fNZNTVy1lnVFRWmY6duiDw6VN0at8a2iW0MW/hEsTHxWGl5zKs37gFnksX4+SJ4yhbzgjuM2fDwMAARYm55Ss3AJw+eRxP/Z9g47bdRVbn65cvsX/PTvTqOwAD/xyGJ48eYdG82VBSUkKb9h1RvkJFDHccA8e//wQAjPhnDMpXqIhRfw2G45hxuHHtCrxWr4CioiLGTpwMu2rVi6xtgPz2t7zm/uRZYACG9O+F1NQUqKmpY96i5ahQ0TTXskYmJnCZNhNmZhZISHiPrZs34s+BvbFz3xEYGGTd62r8JBfMnj4VbVv8AbGiIhREIkyeOh321WoAAOo41EPL1u0wsE93qKioYOoMD6ipqWHuLHdMne6BfXt2YveOrShRQhvOru6oaGpWpHnltb+Z+/fOnZCUihuPX8G5jwOePo/Gm5gP6N7IErUsSyPodUyO8ipKYsz88w/sPv8k37PXRCJg/vAmuPboJZ6EZuUsX6oEAGBK/3pwXnseD569QZ9mlXF8Xk9UG7YBQa9isOnkQ1SuUBJ3vYYgOj4JfWccgramKlwH1EOL8TvgNrA+uv1hieDwWPy94DheRycU+H2Ql/7+EnMz96c2/s65Sb5xgO430qhRI6xatQpA1lLSlStXolWrVvD19YWxsTF27dqFZcuWISgoCAkJCUhPT0fx4tnL2e7du4ehQ4d+9RoLFy7Ehw8fcOvWLVSoUEGyPygoCKmpqahVq5Zkn46ODiwssu9n5efnB0VFRakyurq6sLCwgJ+fn6RMhw4dpK5Zt25dLFmyBBkZGRCLxQCA6tW//Qd7SkqK5F4CnwhiFaioqHzzXFlRUlLCZFc3qX2uU5zRu08/+Ps9wblzZ7F7/yF4b/DC3NkzsWjpchm1tGgxd7b/Z+43EeFYNM8Dy1d7Fem/i8zMTFhaVcaIf7Luz2FRyQrBQYHYv3cX2rTvCADo3K0nOnfrKTnn2OGDUFcvhspVbdG9Qxts3LYLb9++gcukcThw7D8oK+e+nPZXIuv+lpWfJbexiQm27tqPhIQEnDtzCu5TnbHaa3Oug3Q2Ve1gU9VO6nX3zm1xYO8u/D0ya4bn7h1b8ejhfSxcuhKGpUrj7p1bmO8xA/r6JSWzUYcNH4Vhw0dJ6lm3egVq1KoDRUVFbFi3Gjv2HMKVSxfg7joJm3fkvlznV/Oz9Pf/G3Nn+9G5B889ijXjWyF450ikZ2TiXmAEdp/3g93HB0V8oihWwFbXDhCJgH+Wnc53/Uscm8PaRB9N/t0m2afwcW3U+mP3sOXUQwDA/aBz+MPOGANaVMHUDZeQnpGJf5f/h8/vTLVmfGusPHgbVU0N0M7BDDX/3oix3Wth4cim6DX9YIHfA1nh13k25mbu3y13UVL4RZ6Y+jPiEtffSLFixWBqagpTU1PUqFEDXl5e+PDhA9atW4fr16+jT58+aN26NY4ePYq7d+9iypQpUg9YUFNT++Y16tevj4yMDOzeXXSzbQqiWLFi3yzj4eEBLS0tqW3+3LyfTvk57RLaEIvFOW5AGh0dDb08boyvp6eH6I+fzkiV//gpjp6efta+qPzX6etzA0HPAtGzd1/cvOmL+vUbQF1dHc1btsKtm775yvI9mFu+cvs/eYyYd9EY0KsrHKpVgUO1Krhz+yZ279gKh2pVkJGR8e1KcqGnr4/yFStK7TMpXxFvwsNzLR8bEwOvNSsxbtIUPH74AEbGJjAyNkH1GrWQnp6O5589WasoyGt/y2vuT5SUlFHOyBiWVtYY+c9YmJlbYNf2Lfk6V1FJCeYWlnj54jmArIelrFy+BGPGOaF+w0YwM7dA95590LRFK2z94qnEn4SGBOPkscP4e+Q/uHPLF3b21aGto4OmLVrC3+8JPnz4UGRZAfntb+b+/XOHhMei+bgd0G23CGa9V6K+4xYoKSogJDxWUkZRrIBtLh1gVFILbZ125Xv23OJRTdG6VkW0mLADr6LeS/aHv8ua7eYXJv1+PX0ejXIlc793a4OqRrAy1sWqQ3fQwMYIp3yDkZichn0X/VG/qtF3ppYmT/39OeZm7m+18XfITfKNA3S/MZFIBAUFBSQlJeHatWswNjbGlClTUL16dZiZmSEsLEyqvI2NjeSBD3mpWbMmTpw4gdmzZ2PBggWS/RUrVoSSkhJ8fHwk+2JiYhAQkP3EHEtLS6Snp0uViY6OxtOnT2FlZSUpc/XqValrXr16Febm5pLZc/nl7OyMuLg4qW2Ck3O+zlVSVoallTV8blyX7MvMzISPz3WpWRWfs7G1hc+NG1L7bly/BhtbWwBAmbJloaenDx+f7DoTEhLw8MH9XOtMSUmBx8zpcJ02HWKxGJmZGUhPTwcApKelIzOzYIMnX8Pc8pW7eq062L73ELbs2i/ZLK0qo0Xrttiya/93/5v7xKaqPcJCQ6T2PQ8LzfOG+IsXzEGvvv1hYGCIzMxMpKdnP7wmIz0DmQUcKMyLvPa3vObOS2amkO+ngGdkZCDoWQB0P/5in56ejvT0NMktJD4RK4ghZGbmOF8QBHjMdMOY8ZOgrl4MGRkZkq/z9LSs/Pw6LxrMLT+5E5PTEPHuA0poqKBp9fI4ei3rHm+fBucqltFGG6edePfxPnLfsnhUU7Sva46WE3ciLCJO6lhYRBxeR72HeVnpZXGmZXXw/G18jrpUlMRY4tgMo5acQmamALFYBCXFrO8XSooKECsUbnaJPPY3wNzMLR+5Sb5xgO43kpKSgoiICERERMDPzw+Ojo5ISEhAu3btYGZmhufPn2Pnzp0ICgrCsmXLcODAAanz3dzcsGPHDri5ucHPzw8PHz7E3Llzc1zHwcEBx48fh7u7O5YsWQIA0NDQwJAhQzBhwgScO3cOjx49wsCBA6X+eDEzM0OHDh0wdOhQXLlyBffv30ffvn1RpkwZybLWcePG4ezZs5gxYwYCAgKwadMmeHp6Yvz48d/9fqioqKB48eJS2/cs4+s3YBD2792NwwcPIDgoCDOnT0NSUhI6duoMAJjiPBFLF2c/YbZP3/64dvUyNnlvQEhwEFatWI7Hjx6hZ+++ALIGTPv06491a1bhwrmzCAx4ChfnidAvWRKNmzTNcf21q1eiXoOGsLTMGry0tbPH2TP/IeCpP3bu2ApbO/vvfk+Ym7k/V6xYMVQ0NZPa1NTUoKVVQnI/rGkuk7Bi2SLJOWlpqQjw90OAvx/S0tMQ+fYNAvz98OJ59oB/r7798ejhA3h7rcGL52E4dfwoDu7bg649euVog8/1a3gRFoquPXoDACytKyMsNATXrlzCgb27oSBWgJFJ+SLPLo/9Lc+5VyxbhDu3b+L1q1d4FhiQ9fqWL1q2bgsAcHNxkvo691qzAjeuXcWrly/g7/cYblMmIiL8NTp06gog62eefbUaWLZ4Pm7f9MWrVy9x9NABHD96CA0b58x9aP8eaGvroH7DRgCAqrb2uHXTBw8f3MOOrZtQvkJFaBb/+hOUC0Je+5u5f+/cTauXR7Pq5WFsqIXG9iY4uaAXAl68w+ZTD6EoVsD2qR1hb26IQXOOQKygAAPtYjDQLiYZIAOA4/N64O8O2e1Z4tgMPZtYY4DHESQkpkrOUVXOvhvQ4t2+GNGpGjrVt0CF0iUwdUB9WJTTgfeJBzna6NzXAad8g3E/6C0A4PqjV+hQzxyVy+vj7w72uP74VaHfB3npb+ZmbnnM/auT9dNaf+WnuPIedL+RkydPolSpUgCynkZTqVIl7NmzB3/88QcA4N9//8WoUaOQkpKCNm3awNXVFdOmTZOc/8cff2DPnj2YMWMG5syZg+LFi6NBgwa5XqtevXo4duwYWrduDbFYDEdHR8yfP18yIKipqYlx48YhLk76E8iNGzdi9OjRaNu2LVJTU9GgQQMcP34cSkpKAAB7e3vs3r0bU6dOxYwZM1CqVClMnz5d6gER/y8tW7VGzLt3WOm5DFFRkbCoZImVa7yg+3H6c0R4OBRE2b/s2drZw2PeAnguW4LlSxbByNgES5avgJmZuaTMoCFDkZSUhOnTpuL9+3jY2VfDyjU57/8VGBiA0ydPYNe+g5J9zZq3xC1fXwzq3wfGJuUxZ95C/AjMLV+5v+XNF7kj30aiX88uktfbNm/Ets0bYV+tBlat3wQAsKpcBfMWLcPKZYuxfu0qlC5TFv9OmISWbdpJ1Z2cnIwFc2Zi1tyFksF8AwNDjHOaghluU6CsrIyp0z2gqqpa5Lnktb/lNfe7d9Fwd5mEqKhIaGhowtTcHMtWrpM8cfXLr/P4+HjMnuGK6KgoaBbXgqWlFbw2bZe6X93MuQuxctliTJ08AfHxcTAsVRp/jxqDLp/dWxEAoqOjsNFrDbw27ZDss65igz79BuJfx7+ho6MLt+n5u/3C95LX/mbu3zu3lroKpg9pgDJ6mnj3PhmHrjyF28d7wBkZFEc7h6wPmHzXDJY6r/m47bj84AUAoEIpbegWz761y1/ts/7I/m9hb6lzhs4/hq2nHwEAPA/cgqqyGPP+bgxtTVU8DI5EW6ddUktrAcDKRA9dGlZCrb+9Jfv2X/ZH/arlcGZxHwS+iMYAjyOFfh/kpb+Zm7nlMTfJL5EgCIKsG0H0/5KcLusWEP14yWnyOd1eValgS3Lp15SSlnMpqTxQUeLiB/r9abfKuYJDHsSccJJ1E4joB1GVo6lRp55EyroJuWphpS/rJnyTHH2ZEBERERERERHRj/KrLCf9GfFjWCIiIiIiIiIiIhniAB0REREREREREZEMcYkrEREREREREREVmghc41pQnEFHREREREREREQkQxygIyIiIiIiIiIikiEucSUiIiIiIiIiokJT4ArXAuMMOiIiIiIiIiIiIhniAB0REREREREREZEMcYkrEREREREREREVGp/iWnCcQUdERERERERERCRDHKAjIiIiIiIiIiKSIS5xJSIiIiIiIiKiQhNxhWuBcQYdERERERERERGRDHGAjoiIiIiIiIiISIa4xJWIiIiIiIiIiAqNT3EtOM6gIyIiIiIiIiIikiEO0BEREREREREREckQl7gSEREREREREVGhKXCFa4FxBh0REREREREREZEMcQYdEdFvRlVJLOsm0P9RRFyyrJsgE4ZaqrJuAhH9IDEnnGTdBJnQ7rpW1k2QiZi9w2TdBCKinwIH6IiIiIiIiIiIqND4FNeC4xJXIiIiIiIiIiIiGeIAHRERERERERERkQxxiSsRERERERERERWaiCtcC4wz6IiIiIiIiIiIiGSIA3REREREREREREQyxCWuRERERERERERUaFzhWnCcQUdERERERERERCRDHKAjIiIiIiIiIiKSIS5xJSIiIiIiIiKiQlPgY1wLjDPoiIiIiIiIiIiIZIgDdERERERERERERDLEJa5ERERERERERFRoXOBacJxBR0REREREREREJEMcoCMiIiIiIiIiIpIhLnElIiIiIiIiIqLC4xrXAuMMOiIiIiIiIiIiIhniAB0REREREREREZEMcYkrEREREREREREVmohrXAuMM+iIiIiIiIiIiIhkiAN09ENlZGTAwcEBnTt3ltofFxeHcuXKYcqUKQCAAwcOoHbt2tDS0oKmpiasra0xZswYqXrmzJmDSpUqQU1NDTo6OqhVqxa8vLx+aPt3bt+GVs0ao4ZdFfTp2Q0PHzz4avnTp06gQ9uWqGFXBV06tsPlSxeljguCgBXLl6JJw3qoaW+DYUMGIiwsVHI8NTUVkydNgENNe7Rr3QI3rl+TOt97gxc8Zs0osnx5YW7m/hrm/nVyP7x7G1MnOKJX+6Zo4VAV1y6ekzp+5cIZOI/+C11bNkALh6oICvD/Zp0TRg5BC4eqOTbXcaNyLb903gy0cKiK/bu2SvalpqZinvtkdGrqgME92uHOzRtS5+zZ5o0VizwKkDhv8tDfuWFu5v6ab+Wuam2R6+a9Iev3r98198/W3woKIkztXR1+a3ri3a7BeLy6JyZ1t5MqU0xVEYuH1sUzr954t2sw7izvhj9bWH61Xsty2tjh1Az+a3sh6eAwjGpXOUcZDVUlzB9SB0/X9sK7XYNxfk57VDPVlyozpoMNwrz7Icy7H0Z3qCJ1rIaZPq4u7ASxQtHNqPnd+zsvzC1fuUk+cYCOfiixWAxvb2+cPHkS27Ztk+x3dHSEjo4O3NzccPbsWfTo0QNdunSBr68vbt++jVmzZiEtLU1S3t3dHYsXL8aMGTPw5MkTnD9/HsOGDUNsbOwPa/vJE8exYJ4H/hoxEjv3HICFRSUM/2sIoqOjcy1/7+4dTJowDp06d8WuvQfRqHETjHEcicDAAEmZjevXYce2LXBxm4atO3ZDTU0Nw4cNQUpKCgBg755d8Hv8GJu370LXbt0xaeI4CIIAAHj58gX27d0Dx9H//rDMzM3czP175U5OTkIFUwuMGuec+/GkJFhXtcOQEWPyXaerxyLsOHJWsq3Zug8KYjHqN26Wo+zVi2fh//ghdPWk/5g7cWgvAp/6YfHazWjVoSvmuE2SvBcRr1/ixOF9GPiXY/6DfoO89DdzM3dR5z574YrU5j5zNkQiEZo2a/Fb5/7Z+ntc56oY2tIK/669ClvH3XDZ5IOxnapiRBtrSZm5g+ugmX1ZDFpyHraOu+F55CEWD6uLNjWM86xXXUURIRHxcN3si/B3ibmWWTWqARpXLYPBS86j+ui9OHPvFY65t0FpHXUAQGVjHbj2ro7+C89iwKKzcOtdA9bG2gAAsYIIy4bXxz+rriAjUyiS90Ie+pu5mftXJxL9nNuvgAN09MOZm5tjzpw5cHR0RHh4OA4dOoSdO3di8+bNUFZWxpEjR1C3bl1MmDABFhYWMDc3R8eOHbFixQpJHYcPH8aIESPQrVs3lC9fHlWrVsWQIUMwfvz4H9buLZs2onPX7ujYqQsqmprCxc0dqqqqOLh/X67lt23dDId69TFw8J+oULEiRv0zBpZWVti5PWvWiCAI2LZlM4b+NRyNGjeFuUUlzPSYh8i3b3Hu7BkAQEhQEBo2agxTUzP06NUHMe/eISYmBgAwa/o0jBk7HhoaGj8sM3MzN3P/Xrlr1KmHgX+NQt2GTXI93rRVO/Qd/DfsatTKd53Fi2tBR1dPst25eQOqKqpo8MUAXVTkG6xcNAdObrOhqKgkdex5aAhq12sIkwqmaN+lB+JiYxAXm/VeLJs/C0NGjEGxYkX3XshLfzM3cxdlbgDQ09eX2i6cO4saNWuhbLlyv23un7G/a1sY4KhvKE7efoHnbxNw4HoIzt57hepmJaXKbD0fgMuPwvH8bQI2nPbHg9BoVDfTz7Pe288iMXmTD/ZcCUJqekaO46rKYnSsUx5TNvng6pMIBEfEY9bO2wiKiMPQllYAAIuyJfAoNBoXH77GhQev8SjsHSzKlAAA/NupKq4+DsftZ5FF9l7IQ38zN3OT/OIAHf1fODo6omrVqujXrx+GDRuGqVOnomrVqgAAQ0NDPH78GI8ePcrzfENDQ5w7dw6RkUX3A/5r0lJT4ffkMWrXcZDsU1BQQO3aDnhw/26u5zy4dw+1a9eR2udQtx4e3LsHAHj18iWioiJRq3Z2nZqamqhiU1VSp3mlSrh75zaSk5Nx7eoV6OvrQ1tbG8eOHoaKigqaNM05Q6UoMTdzM/fvm/tHOXXkABo2bQlVNXXJvszMTMxzn4KuvQfCpIJpjnMqmJnj8YO7SElJxu0b16Cjpw+tEto4d+oYlJVV8hxQLAh57W/mZu7C5v5SdFQULl+6iE6du0r2/Y65f8b+vvH0DRrZlIFpaS0AQBUTHdSxNMDpOy+kyrStYSyZ2dagcimYldbCmXsvC3xdRQUFKIoVkJwmPXiXnJIBBytDAMCjsHcwLa2FcnrFYKSvAdPSWnj8PAblDTXRv7E5pm27VeDrf0le+vtLzC1fuUm+8Smu9H8hEomwatUqWFpaokqVKpg0aZLkmKOjIy5fvowqVarA2NgYtWvXRvPmzdGnTx+oqKgAABYtWoSuXbvC0NAQ1tbWcHBwQIcOHdCqVas8r5mSkiKZqvyJIFaR1Pk1MbExyMjIgK6urtR+XV1dhIQE53pOVFQUdHX1cpSPio76eDxrcFFXL2edUVFZZTp26oLAp0/RqX1raJfQxryFSxAfF4eVnsuwfuMWeC5djJMnjqNsOSO4z5wNAwODb2b5HszN3J/ayNzSfofcP4L/k4cIDX6GfydPk9q/e+tGiMVidOzeO9fzWrTtiJBngRjauxO0tLQxZcY8vH8fj83rVmLeivXwXuOJC2dOonSZshg7xR16+gV/L+S1v5mbuT+1saC5v3T40AGoqxdDk2bNJft+x9w/Y38v2HcPxdWUcd+zOzIyBYgVRHDbdhM7Lz2TlBm79ipWjGiAoA19kZaeiUxBwIgVl3D1SUSBr5uQnIYb/hFw7m6Ppy9i8SYuCd3rV0Qti5IIiogHADx9GQu3rTdx1L0NAGDqFl88fRmLY+6tMWWzD5rZlcWUntWQlpGJ8V7XCtUeeenvLzG3fOX+Hfwiq0l/Shygo/+bDRs2QF1dHSEhIXj58iVMTEwAAMWKFcOxY8cQFBSE8+fP48aNGxg3bhyWLl2K69evQ11dHVZWVnj06BFu376Nq1ev4tKlS2jXrh0GDhyY54MiPDw84O7uLrVviqsbXKZO+8FJC05JSQmTXd2k9rlOcUbvPv3g7/cE586dxe79h+C9wQtzZ8/EoqXLZdTSosXc2ZibuX+l3KeOHED5imaoZJV9U/BA/yc4uHsbVmzcCVEeN/xQVFTCqPGTpfYtmOmKDt16IyjAH9cuncPqzbuxe5s3Vi6ei6mzF/3QHD/C79jf+cHc2X633AcP7EPrtu2kPuiUh9y5+X/n7lq3Ino2NMXARefw5MU72JTXw/zBdRD+7gO2nQ8EAIxoUxk1LUqiy6yTeP42AfWsS2HJX3UR/i4R5x+8KvC1By85jzWjGiJ4Y1+kZ2TiXlAUdl8Ogl3F7EEQr1N+8DrlJ3ndp5EZEpLS4OP/FvdXdke98QdQRrcYtoxvgkrDdiA1PbPgb4YM8Os8G3P/vrnp58AlrvR/ce3aNSxevBhHjx5FzZo1MWTIEMnNNj+pWLEi/vzzT3h5eeHOnTt48uQJdu3aJTmuoKCAGjVqYMyYMdi/fz+8vb2xfv16hISE5HpNZ2dnxMXFSW0TnHK/UfqXtEtoQywW57gBaXR0NPT09HI9R09PD9FffOocHR0NvY+f4uh9vEl6dFT+6/T1uYGgZ4Ho2bsvbt70Rf36DaCuro7mLVvh1k3ffGX5HszN3N9qI3N/Uf4Xyl3UkpMSceHMKbRo20lq/8P7dxAb8w59O7dEq/r2aFXfHm8iXmPd8oXo3zn3Wc/3bvsiLCQI7bv2xIM7N1HToT5U1dTRoHFzPLhTuOVR8trfzM3c32rjt3J/7s7tWwgNCUHnLt2+2o7fIffP2N+zB9bCgn33sOdKEB6HxWDHhUAsP/IQE7pkPclVVVkM97414LThOo7ffI5HYe+w+vhj7L0SjDEdbQp17ZCI92juchS6PTbA7M9tqD/xIJQUFRDy5n2u5XU1VTClRzWMXXcNNcxL4tmrOASFx+PSo3AoihVgVkarwG2Rl/7+EnPLV26Sbxygox8uMTERAwcOxPDhw9GoUSOsX78evr6+WL16dZ7nmJiYQF1dHR8+fMizjJVV1s1p8yqjoqKC4sWLS235Wd4KAErKyrC0sobPjeuSfZmZmfDxuQ6bqna5nmNjawufGzek9t24fg02trYAgDJly0JPTx8+Ptl1JiQk4OGD+7nWmZKSAo+Z0+E6bTrEYjEyMzOQnp4OAEhPS0dmZs6b+RYWczM3c/++uYvapXP/IS0tFU1atpHa37RlW6zevAervHdJNl09fXTtPQCzFq/KUU9qSgpWLPTA6ImuH9+LTMl7kZGejszMws20kNf+Zm7mLmzuzx3YtxdW1tawqFQpzzb8Lrl/xv5WU1ZE5hcfbGdkClD4OElZSawAZSUxvnxQakamAAWFollslpiSjoiYJJQopoymdmVx1Dc013Lzhjhg+ZGHeBX9AWIFERQVs//cVBQrQKxQ8D8/5aW/v8Tc8pX7tyD6SbdfAAfo6IdzdnaGIAiYM2cOgKzBtwULFmDixIkIDQ3FtGnTMHHiRFy4cAEhISG4e/cuBg8ejLS0NDRrlnUTzq5du2Lx4sXw8fFBWFgYLly4gJEjR8Lc3ByVvvLLYmH0GzAI+/fuxuGDBxAcFISZ06chKSkJHTt1BgBMcZ6IpYsXSsr36dsf165exibvDQgJDsKqFcvx+NEj9OzdF0DWffj69OuPdWtW4cK5swgMeAoX54nQL1kSjZs0zXH9tatXol6DhrC0zBqItLWzx9kz/yHgqT927tgKWzt75mZu5mbur0pKTERQgD+CAvwBABHhrxAU4I+3EeEAgPj4OAQF+OP5x3u5vHgeiqAAf7z77NPnedOnYMOqpTnqPnn0ABzqN0JxrRJS+4trlYBJRTOpTVFRCdq6eihnbJKjnm0b16JGnXowtbAEAFjZ2OLqhbMIfhaAw/t2wrqKbaHfB3npb+Zm7qLM/UlCQgJOnz6JTt+YPfe75P4Z+/v4rTA4dbVDy2rlYFRSA+1rmeCf9lVw2CcUAPA+KQ2XHr3G7AG1UL9yKRiX1ETfxubo84cZDt/IXmniNfoPTO9bQ/JaSVEBNuV1YVNeF8qKCiitUww25XVRwbC4pExT27JoZlcWxiU10bhqGZyc2RYBL2Ox+ezTHO1sXLUMzEprYfXxxwCynhJrUaYEmtuXw+DmlZCRKSDgVWyh3gt56G/mZm6SX7wHHf1QFy9exIoVK3DhwgWoq2c/4e+vv/7C/v37MWTIELi4uGDFihXo378/3rx5A21tbdjZ2eH06dOwsLAAALRo0QI7duyAh4cH4uLiYGhoiMaNG2PatGlQVPwxX8YtW7VGzLt3WOm5DFFRkbCoZImVa7yg+3H6c0R4OBRE2WPctnb28Ji3AJ7LlmD5kkUwMjbBkuUrYGZmLikzaMhQJCUlYfq0qXj/Ph529tWwco1Xjpl9gYEBOH3yBHbtOyjZ16x5S9zy9cWg/n1gbFIec+YtxI/A3MzN3L9P7gD/x5g46k/J6zXLFmRdr3V7jHeZgRuXL2DhrKmS4x5TnQAAfQf/jX5/DgcARL6JgMIXMx5ehIXi8f27mL0k75nQ+REaFIhL505j1abs2xnUb9QMD+7cwrjhg1DWyBiT3OcU6hqA/PQ3czN3UecGgJPHjwGCgFat2+Z57d8t98/W32PXXoNbn+pY+lc96GupITwmEetP+WH27juSMv0XnMX0fjXh/W9jaGuo4HlkAqZtu4l1J7PvDVdOX0NqJl4pHXX4LO4ief1vp6r4t1NVXHr0Gi1cjgIAtIopY3q/miijWwzv3qfg0PUQuG3zRXqG9HQ9VWUxFg+ri34LzuLTJV5Ff8DYdVexxrEhUtMyMHTpeSSnFm7GkTz0N3MzN8kvkfDljcCIfmPJ6bJuARFR0YqIS5Z1E2TCUEtV1k0gIipS2l3XyroJMhGzd5ism0D0w6nK0dSoWyHxsm5CrqqXL/7tQjLGJa5EREREREREREQyxAE6IiIiIiIiIiIiGZKjiZZERERERERERPSjiH6RJ6b+jDiDjoiIiIiIiIiISIY4QEdERERERERERCRDXOJKRERERERERESFxhWuBccZdERERERERERERDLEAToiIiIiIiIiIiIZ4hJXIiIiIiIiIiIqPK5xLTDOoCMiIiIiIiIiIpIhDtARERERERERERHJEJe4EhERERERERFRoYm4xrXAOIOOiIiIiIiIiIhIhjhAR0REREREREREJENc4kpERERERERERIUm4grXAuMMOiIiIiIiIiIiIhniAB0REREREREREdFnVqxYARMTE6iqqqJWrVrw9fXNs+y6detQv359aGtrQ1tbG02bNv1q+dxwgI6IiIiIiIiIiApN9JNu32vXrl0YO3Ys3NzccOfOHVStWhUtWrTA27dvcy1/4cIF9OrVC+fPn8f169dRrlw5NG/eHK9evcr3NUWCIAgFaCvRLyk5XdYtICIqWhFxybJugkwYaqnKuglEREVKu+taWTdBJmL2DpN1E4h+OFU5uvv//efvZd2EXFU10vyu8rVq1UKNGjXg6ekJAMjMzES5cuXg6OiISZMmffP8jIwMaGtrw9PTE/3798/XNTmDjoiIiIiIiIiIflspKSmIj4+X2lJSUnItm5qaitu3b6Np06aSfQoKCmjatCmuX7+er+slJiYiLS0NOjo6+W6jHI3jEhHR70xe54PL60yy1zHyOXOwtLZ89ndKWqasmyATKkr8LF2eyOtMshtB72TdBJmoXTH/f7T/TobsuCfrJsjEtn62sm7C/89P+hRXDw8PuLu7S+1zc3PDtGnTcpSNiopCRkYGDAwMpPYbGBjA398/X9dzcnJC6dKlpQb5voUDdERERERERERE9NtydnbG2LFjpfapqKj8kGvNmTMHO3fuxIULF6Cqmv8PVzlAR0REREREREREvy0VFZV8D8jp6elBLBbjzZs3UvvfvHkDQ0PDr567YMECzJkzB2fOnIGNjc13tZHz5omIiIiIiIiIqNBEP+l/30NZWRnVqlXD2bNnJfsyMzNx9uxZ1KlTJ8/z5s2bhxkzZuDkyZOoXr36d793nEFHRERERERERET00dixYzFgwABUr14dNWvWxJIlS/DhwwcMGjQIANC/f3+UKVMGHh4eAIC5c+di6tSp2L59O0xMTBAREQEA0NDQgIaGRr6uyQE6IiIiIiIiIiKij3r06IHIyEhMnToVERERsLW1xcmTJyUPjnj+/DkUFLIXpa5atQqpqano2rWrVD15PYgiNxygIyIiIiIiIiKiQhP9pE9xLYhRo0Zh1KhRuR67cOGC1OvQ0NBCX4/3oCMiIiIiIiIiIpIhDtARERERERERERHJEJe4EhERERERERFRof1GK1z/7ziDjoiIiIiIiIiISIY4QEdERERERERERCRDXOJKRERERERERESFxzWuBcYZdERERERERERERDLEAToiIiIiIiIiIiIZ4hJXIiIiIiIiIiIqNBHXuBYYZ9ARERERERERERHJEAfoiIiIiIiIiIiIZIhLXImIiIiIiIiIqNBEXOFaYJxB93/wxx9/YMyYMbJuRqF5e3ujRIkSha7nwoULEIlEiI2NLXRdRERERERERES/Og7QFaGBAwdCJBLl2ObNm4cZM2bIunmF1qNHDwQEBHzXObkNTjo4OCA8PBxaWlpF2LofY+f2bWjVrDFq2FVBn57d8PDBg6+WP33qBDq0bYkadlXQpWM7XL50Ueq4IAhYsXwpmjSsh5r2Nhg2ZCDCwkIlx1NTUzF50gQ41LRHu9YtcOP6NanzvTd4wWPWj/9aYm7m/prfJveObWjVvDFq2ldB317d8PDh13PHx8dj9kx3NP2jHmrYVUb7Ni2ksq9ftwa9e3SBQ007NGpQB2P+GYHQkGCpOhbM80ADh5po0aQhjh09LHXs9KkT+Gfk30UXMA/y0N8P792G20RH9OnQFK3qVcW1S+ekjm9dvwpDe3dAx6a10K1lPTiPHgb/x19/HwDgyL6dGNC1Fdo3roExQ/vg6ZOHuZYTBAGu40bkuPb7+Di4TXREp2a1MXJQdzwL8JM6b8XC2di3Y1MBEudNHvr7S3t370Dvbh3QqG51NKpbHYP798S1K5fyLP/3kP6oaWuZY/t31F+SMmtXeaJbx9ZoUNseTerXwsi/BuHRw/uS46mpqXCbMhGN6lZHl/Yt4XtDOvcW7/WYP2dm0Yf9gjz2N8Dcv2vuE3s2YfbYwfinRxOM79caK2c5IeJlmOR41Jtw/NW+Tq7b7Stn86z3yHYvTB3eA47dGuHfXs2x2NURIU8fS5VZMXMCJg3uiJFdGmLCgLbYsMgdsdGRUteeP2k4HLs1wvxJwxH1JlzqfM/p43Dn2vkieiey/O793dnGENv62Upt89tXkhyf0sw0x/HBtcrmWZ9YBPS0K4U5bS2wvlcVeHaxxt8ORiihJr2I0FBTBWP/KI/V3SrDq0cVTG1hCisDDcnxYspijGtUHut7VsGsNuYw1laTOn9gzTJobalfRO8CyTsO0BWxli1bIjw8XGqrVq0aNDU1Zd00pKamFvjctLQ0qKmpoWTJkoVuh7KyMgwNDSH6yee+njxxHAvmeeCvESOxc88BWFhUwvC/hiA6OjrX8vfu3sGkCePQqXNX7Np7EI0aN8EYx5EIDMwe1Ny4fh12bNsCF7dp2LpjN9TU1DB82BCkpKQAAPbu2QW/x4+xefsudO3WHZMmjoMgCACAly9fYN/ePXAc/S9zMzdzF9KpE8excJ4H/ho+Ejv2HIC5RSWM+GsI3uWROy0tFX8PHYTXr15h/qKlOHj0JKZOm4GSJQ0kZW7f8kWPXn2wefturF67Eelp6Rg+bAiSEhMBABcvnMOJY0exau16jBk3AdPdXBAT8w4A8P79e3guWwJnl6k/NLe89HdyUhIqmFpgxFjnXI+XKWeMEf86Y9WmfViw0hsGpUpjytjhiP3YH7m5ePYk1nouQJ9Bf2H5+p0ob2oBl7HDERuT8707uHtrrus7dm5ah6TERCxfvxM2djWwbO50yTG/Rw/w9MlDdOzetwCJcycv/f0lAwNDjPxnLDZt3wvv7XtQvUZtjB8zCkHPAnMtP3fRMhw/c0my7dh7GGKxGE2atZSUMTI2wYRJLtix9xDWbtyKUqXLwHH4n4h5l/U1c2Dfbvj7PYHXph3o1KU7XJ0nSHK/evUSB/fvwfBRY35obnntb+b+fXMHPLqLP9p0waT56zB6+lJkZKRjqdsYpCQnAQB09Epi3qajUlu73n9CRU0d1tXq5FmvQZly6PXXOExdvhUT5q6GbslSWOI2Gu/jYiRlLKrYY9jEmZi+aif+njQbkREvsWbuZMnxvRuWQVtXHy5LN0NLRxf7Ni6XHLt5+QxECgqwd2hUZO+FPPQ3ALyITcKIPY8km/sp6e/b5wKjpI7vuPM6z7qUFRVgoquOAw/fwOVYAJZcDEEpLRWMa1RBqtz4xuWhIAJm/fcMU44/xfOYJIxrXB5aqlkDeR2rGEBVUYwpxwLg9yYBf9YpJznXVE8dFfWK4YR/JCib6CfdfgUcoCtiKioqMDQ0lNqaNGkiNYvMxMQEs2fPxuDBg6GpqQkjIyOsXbtWqp5r167B1tYWqqqqqF69Og4ePAiRSIR79+5Jyjx69AitWrWChoYGDAwM0K9fP0RFRUmO//HHHxg1ahTGjBkDPT09tGjRAgAgEomwatUqtGrVCmpqaqhQoQL27t0rOS80NBQikQi7du1Cw4YNoaqqim3btuVY4jpt2jTY2tpiy5YtMDExgZaWFnr27In3798DyJpRePHiRSxdulQymzA0NDTHEtdP9Z46dQqWlpbQ0NCQDHR+kp6ejn/++QclSpSArq4unJycMGDAAHTs2LGQPZa3LZs2onPX7ujYqQsqmprCxc0dqqqqOLh/X67lt23dDId69TFw8J+oULEiRv0zBpZWVti5fSuArE+ptm3ZjKF/DUejxk1hblEJMz3mIfLtW5w7ewYAEBIUhIaNGsPU1Aw9evVBzLt3iInJ+mVh1vRpGDN2PDQ0NHK9PnMzN3N/R+7Nn+WuaAqXqR9zH8g998H9+xAfF4fFy1bAzr4aypQpi+o1asKiUvYnuyvXrEeHjp1hamoGi0qVMH3WHISHv8aTJ1mfygcHB6F6jZqwrlwFrVq3RbFiGnj18iUAYMmi+ejWoxdKlSr9Y3PLSX/XqFMPA4aNQt2GTXI93qh5a9jVqI1SZcrCuIIphjqOR+KHBIQE5T6AAwAHdm5Bq3ad0bxNRxiXrwjHCS5QUVXF6aMHpcoFBfpj387N+NfZPUcdz8NC0LBpC5Q1MkGr9l3wPCxrhmV6eho8F8zEqAkuEIvFBQ/+BXnp7y/Vb9gIdes3hJGxCYyNy2OE4xioq6tLzXj7nJZWCejp6Us23xvXoKqqiibNW0jKtGzdFjVrO6BM2XKoaGqGMeMm4UNCAgIDnwIAQoODUL9hI1Q0NUPXHr0RE/MOsR9zz53ljlFjxvH7OXMz93ca7b4EDk3aoLRRBZQrb4aBo13wLjICYc/8AQAKYjG0tHWltnvXL6J63cZQVVPPs96aDVvA0rYm9A3LoLRRBXQbMhrJiR/wMvSZpEzTDr1QoVJl6JYshYqWNmjZpT9Cnj5GRno6ACDiZShqN24Fg9Ll4NCkDcJfhAIAEhPe4/DWNej11/giex8A+ehvAMjMBOKS0yVbQkqG1PGUdEHqeFJaZp51JaVlYs6ZIPiExSI8PgXPohKxyfclKuiqQ1ddCQCgoSJGqeKqOPL4LV7EJuPN+1TsvBMOVUUxypZQBQCU1lLFjdAYRLxPwbmAaJTWUgGQNUNvcK1y2HDjBT6OWxIVGgfoZGThwoWoXr067t69ixEjRmD48OF4+jTrl7z4+Hi0a9cOVapUwZ07dzBjxgw4OTlJnR8bG4vGjRvDzs4Ot27dwsmTJ/HmzRt0795dqtymTZugrKyMq1evYvXq1ZL9rq6u6NKlC+7fv48+ffqgZ8+e8POTXmozadIkjB49Gn5+fpLBvS8FBQXh4MGDOHr0KI4ePYqLFy9izpw5AIClS5eiTp06GDp0qGQ2Ybly5XKtJzExEQsWLMCWLVtw6dIlPH/+HOPHZ/9gmzt3LrZt24aNGzfi6tWriI+Px8GDB/P3ZhdAWmoq/J48Ru06DpJ9CgoKqF3bAQ/u3831nAf37qF2belP6xzq1sODj4Oqr16+RFRUJGrVzq5TU1MTVWyqSuo0r1QJd+/cRnJyMq5dvQJ9fX1oa2vj2NHDUFFRQZOmzYo4qTTmZm65yJ2WlfvzNiooKKDWV3JfuHAONlVt4TFrOho3cECXjm3htXY1MjIyci0PAAkJWR9WfFrOb2FRCU8eP0J8XByePH6ElJRkGBkZ4+6dW/B78hi9+/QrwpQ5yWt/f0taWhpOHNqHYhqaqGBqnmeZwAA/2FavLdmnoKAA2+q14ffZ0tjk5CTMdXfGyLGToaOrl6OeCqbmuH/7JjLS03Hb9xrKV8y63p5t3qhiVx3mlayLLhf7GwCQkZGB0yePISkpEVVsbPN1zuGD+9CsRWuo5fEHflpaKg7u2w0NDU2Ym2cN0ptZVML9u3eQnJyMG9euQE9fHyW0tXHy2BEoK6ugUWN+P/8RmFu+cid9SAAAFNMsnuvxsGf+eBESiLrN2uW7zvS0NFw+dRBqxTRQrrxZrmU+vI+Dz8VTqFCpCsSKWbOqypqYwf/+TWRmZuLJXR+UNTEFAOzz9kTD1l2go2+Qa10FIU/9bVBcGZ5drLG4oyVG1DOSDKR9Ure8NlZ3q4w57SzQw64UlMXfNy9KTUmMTEFAYlrW728JKRl4HZeM+hV0oKKoAAUR0NhcF3FJaQh5lzVT83lMEqwMNaAgAmxKF8eLmGQAQFtrAzx5kyApR1QU+BTXInb06FGpTxJatWqVa7nWrVtjxIgRAAAnJycsXrwY58+fh4WFBbZv3w6RSIR169ZBVVUVVlZWePXqFYYOHSo539PTE3Z2dpg9e7Zk34YNG1CuXDkEBATA3Dzrl34zMzPMmzcvx/W7deuGP//8EwAwY8YM/Pfff1i+fDlWrlwpKTNmzBh07tz5q3kzMzPh7e0tWcLbr18/nD17FrNmzYKWlhaUlZWhrq4OQ0PDr9aTlpaG1atXo2LFigCAUaNGYfr07KU/y5cvh7OzMzp16iTJf/z48a/WmZKSIpmi/YkgVoGKispXzwOAmNgYZGRkQFdXV2q/rq4uQr64p9QnUVFR0P3iDzJdXV1ERUd9PJ419VlXL2edn2Y+duzUBYFPn6JT+9bQLqGNeQuXID4uDis9l2H9xi3wXLoYJ08cR9lyRnCfORsGBkX3wx9gbubObuNvnTsm79xf3jPuk1cvX+Dmqxto3aYdPFetxYvnzzF7pjvS09Px94hROcpnZmZi/pzZsLWzh6lZ1vdjh7r10bpte/Tp2RUqqqqYMWsu1NTVMGuGO6bP9MCeXTuwY/sWlCihDddpM2BqmvsfCgXOLaf9nRefqxcxZ5oTUpKToaOrh1mLV0OrhHauZePjYpCZkQFtHemc2jq6eBkWInm9dtl8WFWuijr1c1/W1L3vYHgumIXBPdqiZKnSGDNpGl69CMPZE4exaM0WLJ8/A3d8r8OskjVGO01FMY2C3x5D3vv7WWAAhvTvhdTUFKipqWPeouWoUNH0m+c9fvgAQc8C4eKW835xly+dh4vTeCQnJ0FPTx+eq9ejhHbW10z7Dp3xLOApenRuixIltDF73mLEx8dhzarlWO21Cas8l+C/UydQpmw5uE6bhZL8fl4kmFt+cmdmZmK31xJUtLRBGeOKuZa5+t8RlCpngoqWNt+s78HNK/CaPxWpKcnQ0tbFmOlLoVG8hFSZfd4rcOHYXqSmJKO8RWWMcl0gOdZl8ChsWzEXk//sjLImFdFnpBMCHt3Fi+BAdB4wAmvnTkHYM39Y2dVEj6FjoaikhIKSl/4OivqANVeTEB6fghJqSuhsY4ipLczgdMQfyemZuBYag6iEVMQmpaGcthp62ZVCqeIqWHIxNF/1KymI0Mu+NK6HxkjNvPM4E4R//ygPr55VIAhAfHI65p4NRmJq1iDe4UdvMLhWOSzuaIXID6lYd/05DDSVUb+iNqadCMTgWmVRpZQmgqMT4XXjxVdn9cmNX2U96U+IA3RFrFGjRli1apXkdbFixdCrV68c5Wxssn9wiEQiGBoa4u3btwCAp0+fwsbGBqqqqpIyNWvWlDr//v37OH/+fK7TioOCgiQDdNWqVcu1nXXq1Mnx+vPlswBQvXr1XM/9nImJidT99UqVKiXJ8T3U1dUlg3Nf1hMXF4c3b95IvQdisRjVqlVDZmbe3wA9PDzg7i69xGiKqxtcpk777vb9vygpKWGyq5vUPtcpzujdpx/8/Z7g3Lmz2L3/ELw3eGHu7JlYtHR5HjX9Wpg7G3P/nLkzMwXo6OjCddoMiMViWFlXxtu3b7Bp4/pcB+g8Zrrj2bNAeG/eLrV/+EhHDB/pKHm9eqUnatWuA0VFRaxbswp7DhzBpYvn4TrZCTt27//huf4fftb+rmpfAys27kZcbCxOHtkHj6kTsGTtVpTQ1v32ybm4ceUC7t+5Cc8Nu/IsU0xDE07T5kjtm/TPnxgycizOnz6G8NcvsW7HISydOx3bN67BUMeiXSL1//Cz9LexiQm27tqPhIQEnDtzCu5TnbHaa/M3B+kOH9wHUzNzWFfJ+Qd+9Rq1sHXXfsTGxuDg/j1wnvgvNm7dBR0dXSgqKWHiZOl7SE6fOhk9evXFU38/XDx/Ftt2H8CWjeuxcN4szF24rEjzysrP0t//b8yd7f+Ve8fqBXj9PBgT5qzJ9XhqSjJ8L51Gm+6D8lWfRZVqcFmyCQnxcbhy+hDWznXBpAVeKF5CR1KmRec+qNesHaLfRuDozvXYuGQ6RrkugEgkgrZuSYyaulBSNi0tFcvc/sXAMa44ttsbqmrqmL5qF5ZOG4NLpw6icdtuhXsDZOD/3d/3X7+X/P8XsckIikrE0s5WqGVSAhefvcP5wGip47FJaZjSzBQlNZTxNuHr91oXiwDHBiYAgI0+L6WODaxZFvHJ6Zhx6hlSMzLxh6kuxjcqD9cTAYhNylpGu+JKmNQ5k5tVxI7br1G3gjZKaihj/CE//FnHKOtBF7fzvi8e0bdwiWsRK1asGExNTSVbqVKlci2n9MWnKCKR6KuDTV9KSEhAu3btcO/ePaktMDAQDRo0kGpPQeXn3MLm+Fo9QiEX8zs7OyMuLk5qm+CU+w3Dv6RdQhtisTjHjVejo6Ohp5dz2RIA6OnpITo6Kmf5j59e6ellPd0nOir/dfr63EDQs0D07N0XN2/6on79BlBXV0fzlq1w66ZvvrJ8D+Zm7m+18bfIrf39ufX19WFsYiJ1f7DyFSogKioSaWnSvxR6zJqOSxcvwGvDJhh8ZfZwSHAQjh09jJGOo3Hrpi/sq1eHjo4OWrRoBb8nj/Hh41KeoiKv/Z0XVTV1lC5rBMvKNvjX2R1isSJOfXE/uU+Ka2lDQSxGzDvpnDHvoqH98b24d9sX4a9eoGuremjT0B5tGtoDAGa5jMPEUUNyrff0sYMopqGJOvUb4cHdW3Co3xiKikqo36gZHty9Vah88t7fSkrKKGdkDEsra4z8ZyzMzC2wa/uWr56TlJSI06eOo33HLrkeV1NTRzkjY1SxsYXrtFlQFItxOI/7Vt666YPgoGfo1rMPbt/yhUO9BlBTU0eT5i1x+xa/nxcV5paP3DtWL8DDW1cxduYKaOvl/sC6O9fOIzUlGbUb57566UsqqmooWbocKlSqjP7/TIFYLMbV/45IldEoXgIGZYxgZVcTQyfMwKNb1xD89FGu9Z3YswmWdjVhbFoJAQ/vwM6hEcSKirCr8wcCHt75vsBfkLf+/iQxLQPh8Skw1Mx99VNQVNZDuAzyOP7Jp8E5vWLKmHMmSGqGm7WhBuzKFIfn5VAERH5A6LskePu+RGqGgPoVdHKtr0FFHSSmZuD2y3hYGmjg1os4ZAiAT1gsLA1yTp4h+h4coPsJWVhY4OHDh1LLM2/evClVxt7eHo8fP4aJiYnUgKCpqWm+BtZu3LiR47WlpWXRBPiMsrLyV+/RlB9aWlowMDCQeg8yMjJw587Xf9ipqKigePHiUlt+lrcCgJKyMiytrOFz47pkX2ZmJnx8rsOmql2u59jY2sLny/f1+jXY2NoCAMqULQs9PX34+GTXmZCQgIcP7udaZ0pKCjxmTofrtOkQi8XIzMxA+scb06anpSMzs3Dva26Ym7nlIrdSVm5fH+ncvl/JXdXWHs+fP5f6ACIsNBT6+vpQUlIGkHXDZY9Z03Hu7H9Yu2ETypTN/Z6bn8rOnO6G8RMnQV29GDIyM5GelpU77WP+jIyiXSIhr/2dX5mZmUjL42nnSkpKMDO3xL3bPlLl7932gaV11kyr7n0HY+WmPVixcZdkA4BhjuMxdnLOB0bExrzDdu81GP7vJEl9kvciPb1AH3ZJtZn9LSUzU/jm0+zPnj6FtNRUtGyTv/tXZQq515mSkoL5HjPg7DotK3dGdt9mpKcjs4j/bQPy29/M/XvnFgQBO1YvwL0bF/HvTE/oGeb9IKWr/x1B1Zr1oamV+60KviVTEJCelvaVtmT9u82tTPiLUNy8eBod+gzLKpuZKXmYRAa/nxeYiqICDDSVEZuUe78Ya6sBQJ7HgezBOcPiKvA48wwJqdLtVFbMGg7J/GJeSKYg5PYwdmiqiNHJxgCbfF8BABREIogVsgqKFURQyO0kOST6Sf/7FXCA7ifUu3dvZGZmYtiwYfDz88OpU6ewYEHWPQ9EH//Rjxw5Eu/evUOvXr1w8+ZNBAUF4dSpUxg0aFC+BsT27NmDDRs2ICAgAG5ubvD19cWoUTmXaRWWiYkJfHx8EBoaiqioqAL/gHJ0dISHhwcOHTqEp0+fYvTo0YiJiZG8Hz9CvwGDsH/vbhw+eADBQUGYOX0akpKS0LFT1n35pjhPxNLF2VPb+/Ttj2tXL2OT9waEBAdh1YrlePzoEXr27gsgq+/69OuPdWtW4cK5swgMeAoX54nQL1kSjZs0zXH9tatXol6DhrC0tAIA2NrZ4+yZ/xDw1B87d2yFrZ09czM3cxc0d/+PuQ9l5Z41Iyt3h45ZuV2cJ2LZZ7m79+iF+LhYzJszC2GhIbh08QLWr1uD7j37SMrMnumOY0cPw2PuQhQrVgxRUZGIiopEcnJyjuvv37cH2to6aPhHY0num7438OD+PWzd7I0KFU1RvHjuN8EuVG456e+kxEQEBfojKDDrSX9vwl8hKNAfbyPCkZyUCO81y+D36AHeRLxGoP8TLJo9FdFRb1G/UfYNryeNHorD+3ZIXnfq2Q8nj+zHfycO43loMDwXzERKUhKatekIANDR1YNJBTOpDQD0DUrBsHTZHG1cs2w+OvfsD72PNxK3qmKLc6eO4nloME4c3gerKraFfh/kpb+/tGLZIty5fROvX73Cs8CArNe3fNGydVsAgJuLE1YsW5TjvEMH96FhoyYo8cW9CJOSErFy2WI8fHAP4a9fwe/JY8xwm4LIt2/QpFnOh2itX7sKDvUawKJSVm4bWztcOPcfAgOeYveubahqm/sf1IUlr/3N3L9v7h2rF8Dn4ikMGe8OVTV1xMVEIy4mGqkp0j9X375+gcDH9/J8OMTU4T1w9/oFAEBKchIObF6FYP9HiH4bjrBn/ti0dCZioyNRrV7Wz+SQp49x/ugevAgOQPTbcPjfvwWv+VOhb1gGFSpVlqpbEARsXTEH3f4cDRXVrAGjipY2uHL6EMJfhOLG+ROoaFml0O+FPPR3b/vSqFSyGPSKKcNMXx3//lEemQJwLSQGJTWU0bGKAUx01KBXTBn2ZYvj77pG8HuTgBex2V8P89tXQvVyWQ/nEouA0Q3Lo4KuOlZeCYOCSAQtVUVoqSpKBtUCIz/gQ2oG/nYwgpG2Kgw1VdDLvjRKaijj3qv4nP1QowyOP4lEzMdBwYC3H1Cvgg5KF1dBYzNdBEQW7eoHkj+8B91PqHjx4jhy5AiGDx8OW1tbVKlSBVOnTkXv3r0l96UrXbo0rl69CicnJzRv3hwpKSkwNjZGy5YtoaDw7XFXd3d37Ny5EyNGjECpUqWwY8cOWFlZFXmW8ePHY8CAAbCyskJSUhJCQkK+fVIunJycEBERgf79+0MsFmPYsGFo0aKF1HKzotayVWvEvHuHlZ7LEBUVCYtKlli5xgu6H6d9R4SHQ0GU/V7b2tnDY94CeC5bguVLFsHI2ARLlq+AmVn2UwEHDRmKpKQkTJ82Fe/fx8POvhpWrvHKMbMvMDAAp0+ewK59ByX7mjVviVu+vhjUvw+MTcpjzryF+BGYm7nlIXeLVq0RE/MOqz7PvTo7d3h4OESffS81LFUKK9esx4J5HujWuT1KljRA7779MWhI9sN79uzKGsz5c5D001jdZ3pIBv4AIDoqCl5rV2PT1uzBnypVbNBvwCA4jvgLOjo6mD577g/JLS/9Hej/GE7//Cl5vXZ51odcTVu1h+N4F7wIC8GZE4cRFxeL4sVLwNzSGvNXbIRxhez7k4W/eon42FjJ64ZNWiIuNgZbvVbi3bsoVDS1wIyFK3M8OCI/bvtcRfjL55jgOkuyr12Xngj0f4Ixw/rCwrIy+gz+qwDJpclLf3/p3btouLtMQlRUJDQ0NGFqbo5lK9ehVp26AIA3X+QGgLDQENy/exvLV3nlqE9BQYzQ0GAcG3cQsbEx0CpRAlbWVbB2w1ZU/OJhLkHPAnD29Als3X1Asq9Jsxa4c8sXwwb3hbFxeczwmP8DUstvfzP375v74omse7EunDxSav+A0S5waNJG8vrqmaMooVsSVna1cq3nzavnSEr8ACDr6acRL8Nw49xxJMTHoVhxLZiYWmLCnFUobVQBAKCsooK71y/iyA4vpCRnPUTC2r42hvYYKJk1/8nlUwdRvIQObGrUk+xr22sI1i90w5zxQ2BtXxuN2nQt9HshD/2tU0wJo+qbQENFjPfJ6Xga+QFuJwLwPiUDSmIFVC6liZaW+lBRVMC7D2m4+TwWBx++kaqjtJYq1JWy/j7UVldGtY+DdR5tK0mVm3n6GfzeJCAhJQNzzwahu10pTG5mCkWRCC/jkrHoQgiex0gPBFcppQkDTRWsuvJcsu/000iU11XD9FbmCIpOxP4H0u0h+l4iobA3+qL/i23btmHQoEGIi4uDmppaoeoSiUQ4cOAAOnbsWDSNk4HMzExYWlqie/fumDFjRr7PS07/gY0iIpmS159m8rqa4nVMzpmJ8qC0tuq3C/2GUuT0qXgqSlzsQr+/G0HvZN0EmahdMfd7nP3uhuy4J+smyMS2fraybsL/zdOIRFk3IVcWhuqybsI3cQbdT2rz5s2oUKECypQpg/v378PJyQndu3cv9ODcryosLAynT59Gw4YNkZKSAk9PT4SEhKB3796ybhoRERERERERUaFwgO4nFRERgalTpyIiIgKlSpVCt27dMGvWrG+f+JtSUFCAt7c3xo8fD0EQULlyZZw5c+aHPNiCiIiIiIiIiOj/iQN0P6mJEydi4sSJP6TuX3FVc7ly5XD16lVZN4OIiIiIiIiI8iCnd18pEryxBRERERERERERkQxxgI6IiIiIiIiIiEiGuMSViIiIiIiIiIgKj2tcC4wz6IiIiIiIiIiIiGSIA3REREREREREREQyxCWuRERERERERERUaCKucS0wzqAjIiIiIiIiIiKSIQ7QERERERERERERyRCXuBIRERERERERUaGJuMK1wDiDjoiIiIiIiIiISIY4QEdERERERERERCRDXOJKRERERERERESFxhWuBccZdERERERERERERDLEAToiIiIiIiIiIiIZ4hJXIiIiIiIiIiIqPK5xLTDOoCMiIiIiIiIiIpIhDtARERERERERERHJkEgQBEHWjSD6f0lOl3ULiIiIiIhI3mnXGCXrJshEzE1PWTdBJlTl6OZiwZHJsm5Criroq8q6Cd/EGXREREREREREREQyxAE6IiIiIiIiIiIiGZKjiZZERERERERERPSjiPgU1wLjDDoiIiIiIiIiIiIZ4gAdERERERERERGRDHGJKxERERERERERFRpXuBYcZ9ARERERERERERHJEAfoiIiIiIiIiIiIZIhLXImIiIiIiIiIqPC4xrXAOIOOiIiIiIiIiIhIhjhAR0REREREREREJENc4kpERERERERERIUm4hrXAuMMOiIiIiIiIiIiIhniAB0REREREREREZEMcYkrEREREREREREVmogrXAuMM+iIiIiIiIiIiIhkiAN0REREREREREREMsQlrkREREREREREVGhc4VpwnEFHREREREREREQkQxyg+wUMHDgQIpEIIpEISkpKMDAwQLNmzbBhwwZkZmZKypmYmEjKqampwcTEBN27d8e5c+e++5qRkZEYPnw4jIyMoKKiAkNDQ7Ro0QJXr17N1/kikQgHDx7MNUvHjh0lr//44w9Jm1VUVFCmTBm0a9cO+/fvz7XOT5uWlhbq1q1boGzfY+f2bWjVrDFq2FVBn57d8PDBg6+WP33qBDq0bYkadlXQpWM7XL50Ueq4IAhYsXwpmjSsh5r2Nhg2ZCDCwkIlx1NTUzF50gQ41LRHu9YtcOP6NanzvTd4wWPWjCLLlxfmZu6vYW7m/hxzMzdzMzdzMzfA3AVV174i9i75C8GnZyHprifa/WGTo4zr8DYIPj0L764vwrHVo1DRSF/quHZxdWycNQBvLs9H+KV5WOXWG8XUlL96XRVlRSye1B0vz89F5NWF2LHgT5TU0ZQqU85QG/uX/Y3oa4sQdtYDs8d0hFicPYRQ1aIsru9wQuTVhdi75C9oF1eXHBOLFXB120RUtzYuyNsi8bv1N9FXCfTTGzBggNCyZUshPDxcePnypXD79m1h1qxZgoaGhtCqVSshLS1NEARBMDY2FqZPny6Eh4cLYWFhwsWLF4WhQ4cKIpFImDlz5ndds379+kKtWrWEc+fOCaGhoYKPj48we/Zs4dChQ/k6H4Bw4MCBXLN06NBB8rphw4bC0KFDhfDwcOHFixfC9evXhYkTJwpKSkrC0KFDc9S5ceNGITw8XHj48KHQvn17QU1NTQgKCsp3rqS0/G8HDh8TrK2thR279wqP/AIF58kuQrXq1YWXEVG5lr/ue1uwtLQUVq1ZJzz2fybMX7hYsLKyFh48eSops2LVGqFatWrC8VP/Cfcf+QnD/vpbaNS4sRCbkCwkpQnCeu/NQsuWrYSHfgHC6rVeQq3atYXE1EwhKU0QAkOeC02bNRciY95/V47v3ZibuZmbuZmbuZmbuZmbuZn7x+ZWtR0pqNqOFNqPXCF4rD0hdP93jSAIgtBtzBrJMVXbkcKUJQeEmPgPQtcxq4Xq3WYJh8/fF4JfRApaNUdLypy88ki45/9CqN93ntB44EIhMOyNsPP4Tal6vtzW7L4kPH8dLbQYulSo02uOcON+sHDt7jPJcXX7UcLDgFfCmet+Qs3us4X2I1cIb9/FC3O9TkrK3H4cJizZfEao3N5duHw7UFi86YxUu1dsP5/juvLa3/Lkxbvkn3L7FXCA7hfw5aDWJ2fPnhUACOvWrRMEIWuAbvHixTnKTZ06VVBQUBD8/f0l+y5cuCDUqFFDUFZWFgwNDQUnJyfJQF9MTIwAQLhw4UKB2/w9A3SjR4/OUW7Dhg0CAOG///7Ls85Xr14JAITVq1fnu13f8020c5eugqubu+T1h5QMoW69eoLnyjW5lh/1z2hhyNBhUvu6dO0mTHZxFZLSBCExNVNwcKgrrF7rJTn+9l28ULlyZWH/oaNCUpoguLi6CR5z5wtJaYIQ8z5JMDc3F169iRaS0gRh4KDBwtETp3/oLz3MzdzMzdzMzdzMzdzMzdzM/eNz5zZoJgg5B+hev40VJi3cL3ldst44ISk5VejntEFQtR0pVO00XRAEQXDoPVdSpt0ITyEjI0Mo32xyrtcpWW+ckJKaJvQav06yz6ZjVj0N+s2XDBymp2cIRo0nScqMmrlDiI1PFDSr/yOo2o4UPiSmCDYdpwuqtiMFx1k7hOOXHgqqtiOFSm2mCgGhbwQ9h7GFGqD7nfpbnsh6IO5XHqDjEtdfWOPGjVG1atVcl4N+bvTo0RAEAYcOHQIAvHr1Cq1bt0aNGjVw//59rFq1CuvXr8fMmTMBABoaGtDQ0MDBgweRkpLyw3PkZsCAAdDW1v5qNjU1NQBZ05CLWlpqKvyePEbtOg6SfQoKCqhd2wEP7t/N9ZwH9+6hdu06Uvsc6tbDg3v3AACvXr5EVFQkatXOrlNTUxNVbKpK6jSvVAl379xGcnIyrl29An19fWhra+PY0cNQUVFBk6bNijipNOZmbuZm7s8xdzbmZm7mZm7mZu7/d26TMroopa+Fcz7+kn3xCcm4+SgUtWxMAAC1bMojJj4Rd548l5Q55/MUmZkCalTOfXmpnaURlJUUce7GU8m+gNA3eB7+DrVsykvqffTsNd6+ey8p8981P2hpqsGqYikAwMPAV2hSuxLEYgU0qmmBR4GvAQDLp/TElCUHkZBY8L8l5bG/ifgU119cpUqV8OAb6/B1dHRQsmRJhIaGAgBWrlyJcuXKwdPTEyKRCJUqVcLr16/h5OSEqVOnQlFREd7e3hg6dChWr14Ne3t7NGzYED179oSNTc57IvwICgoKMDc3l7T5S4mJiXBxcYFYLEbDhg2L/PoxsTHIyMiArq6u1H5dXV2EhATnek5UVBR0dfVylI+Kjvp4PDJrn17OOqOissp07NQFgU+folP71tAuoY15C5cgPi4OKz2XYf3GLfBcuhgnTxxH2XJGcJ85GwYGBkWS9xPmZu5PbWRuacz9RSbmztrH3NllmJu5mZu5mbvIcxvqFQcAqUEyAHgb/R4GulnHDHSLI/KL4xkZmXgXnwiDj+fnqFe3OFJS0xCXkPRFvfFS9b6N/uK67+KzjukVB54Cw923YenkHhjTvwmu3wvG/A2n0atNDSQlp+L24zAcXjESFcrqYc+p23BfefS7sstjf/8++BzXguIA3S9OEASIRN/+B/B5OT8/P9SpU0fqvLp16yIhIQEvX76EkZERunTpgjZt2uDy5cu4ceMGTpw4gXnz5sHLywsDBw78UXHybPMnvXr1glgsRlJSEvT19bF+/fo8Bw1TUlJyzAAUxCpQUVH5YW0uLCUlJUx2dZPa5zrFGb379IO/3xOcO3cWu/cfgvcGL8ydPROLli6XUUuLFnNnY27mZm7m/pUxdzbmZm7mZu7fnV9wBJr/uVTyWkerGFz/boNmQ5ZgkVM33LgfjJ7j1uHKtgm4+SgUxy89kmFr84f9TbLEJa6/OD8/P5QvX/6rZaKjoxEZGfnNcl9SVVVFs2bN4OrqimvXrmHgwIFwc3P79onImiocFxeXY39sbCy0tLS+eX5GRgYCAwNztHnx4sW4d+8eIiIiEBERgQEDBuRZh4eHB7S0tKS2+XM98tV+7RLaEIvFiI6OltofHR0NPT29XM/R09ND9MdPZ6TKf/wUR08v62lL0VH5r9PX5waCngWiZ+++uHnTF/XrN4C6ujqat2yFWzd985XlezA3c3+rjcz9RXnmztrH3N+sk7mZm7mZu6gwt/zkjojKmrH25dNVS+pq4k101rE30fHQ/+K4WKwAneLqePPx/Bz1RsdDRVkJWhpqX9RbXKrekrpfXFcna3ZdXvXOHdcZntvP49XbWNSvbob9Z+4iMTkVJy8/RoPqZvmJLCGP/U3EAbpf2Llz5/Dw4UN06dLlq+WWLl0KBQUFdOzYEQBgaWmJ69evQxAESZmrV69CU1MTZcuWzbMeKysrfPjwIV9ts7CwwO3bt6X2ZWRk4P79+zA3N//m+Zs2bUJMTEyObIaGhjA1NYW+vn4eZ2ZzdnZGXFyc1DbByTlf7VdSVoallTV8blyX7MvMzISPz3XYVLXL9RwbW1v43Lghte/G9WuwsbUFAJQpWxZ6evrw8cmuMyEhAQ8f3M+1zpSUFHjMnA7XadMhFouRmZmB9PR0AEB6WjoyMzPyleV7MDdzMzdzf465szE3czM3czN3Nub+/+QOfRWN8Mg4NKplIdmnWUwVNSqbwOdBKADA50EItIurw86ynKTMHzXMoaAgws1HYbnWe9fvOVLT0qXqNTMuCaNSOvB5ECKpt7Jpaehra0jKNKldCXHvk+AXHJGjzj9qmqNSeQOs2nkJACBWUICSohgAoKQohljh+4Ye5LG/fxci0c+5/Qo4QPeLSElJQUREBF69eoU7d+5g9uzZ6NChA9q2bYv+/ftLyr1//x4RERF48eIFLl26hGHDhmHmzJmYNWsWTE1NAQAjRozAixcv4OjoCH9/fxw6dAhubm4YO3YsFBQUEB0djcaNG2Pr1q148OABQkJCsGfPHsybNw8dOnTIV3vHjh0LLy8vrFy5EoGBgbh37x6GDRuGmJgY/Pnnn1JlExMTERERgZcvX+LGjRtwcnLC33//jeHDh6NRo0YFfs9UVFRQvHhxqe17lrf2GzAI+/fuxuGDBxAcFISZ06chKSkJHTt1BgBMcZ6IpYsXSsr36dsf165exibvDQgJDsKqFcvx+NEj9OzdFwAgEonQp19/rFuzChfOnUVgwFO4OE+EfsmSaNykaY7rr129EvUaNISlpRUAwNbOHmfP/IeAp/7YuWMrbO3sC/zeMDdzMzdzMzdzMzdzMzdzM7fscxdTU4aNeRnYmJcBkPVgCBvzMihnqA0AWLH9PJz+bIk2DavA2rQ01s/oh/DIOBw+fx8A8DTkDU5dfYwVrr1R3doYdapWwOJJ3bHn1B2ER2ataCqtr4V7+11Q3TrroRHxCcnwPngdc8d1RoPqZrCzLIe17n1x434wfB+GAgDOXPeDX3AE1s8cgCrmZdC0jiXcRrbFmt2XkJqWLpVBRVkRi526Y+SMHZJJINfvB+Ov7g1QxbwMOjaxxfV7ud837mt+x/4m+ipZPkKW8mfAgAECAAGAoKioKOjr6wtNmzYVNmzYIGRkZEjKGRsbS8opKysLRkZGQvfu3YVz587lqPPChQtCjRo1BGVlZcHQ0FBwcnIS0tKynv+cnJwsTJo0SbC3txe0tLQEdXV1wcLCQnBxcRESExPz3e5t27YJ1apVEzQ1NQUDAwOhdevWwv3796XKNGzYUKrNpUqVEtq2bSvs378/R30AhAMHDuT7+rn53sdhb/DeIjRs+IdgbW0tdO7SVfC5fU9yrHefvsL4CU5S5Q8dPS40a95csLa2Flq1biOcPntB6nhiaqawYNESoU4dB6Fy5cpCv/4DBL/A4BzXffDkqdC0aTMhOu6D1GPFXVzdBHt7e6FT5y7C02ehP+wR9szN3MzN3MzN3MzN3MzN3Mz943Kr2o4UVG1HCs2GLMn175bNh65Lysxac1wIj4wTkpJThbM3/ITK7d0lx1RtRwqlGkwQdh6/KcQnJAmx8YmC94Frgm6dfyXHzVu5CoIgCM2GLJHs06o5Wli186IQHZsgJCQmCwfP3BWMm0ySqte8lYtw4vIj4UNiivD2XbyweNMZoVg1R6kyqrYjhXnrTwmLN52R2mfVzk24+TBEiI1PFFbvuiio2Y0SVG1Hym1/y5OXMSk/5fYrEAnCZ+sciX5zyenfLkNERERERPQjadcYJesmyETMTU9ZN0EmVOXo8ZyvY1Nl3YRclS6hLOsmfBOXuBIREREREREREckQB+jou23btg0aGhq5btbW1rJuHhERERERERHRL0WOJlpSUWnfvj1q1aqV6zElJaX/c2uIiIiIiIiI6Gfwqzwx9WfEATr6bpqamtDU1JR1M4iIiIiIiIiIfgtc4kpERERERERERCRDnEFHRERERERERESFJgLXuBYUZ9ARERERERERERHJEAfoiIiIiIiIiIiIZIhLXImIiIiIiIiIqPC4wrXAOIOOiIiIiIiIiIhIhjhAR0REREREREREJENc4kpERERERERERIXGFa4Fxxl0REREREREREREMsQBOiIiIiIiIiIiIhniElciIiIiIiIiIio0Ede4Fhhn0BEREREREREREckQB+iIiIiIiIiIiIhkiEtciYiIiIiIiIio0ER8jmuBcQYdERERERERERGRDHGAjoiIiIiIiIiISIZEgiAIsm4E0f9LcrqsW0BERERERCSftGuMknUTZCLprqesm/B/E5nwc/7Rra/x89/hjTPoiIiIiIiIiIiIZIgDdERERERERERERDL088/xIyIiIiIiIiKinx6f4VpwnEFHREREREREREQkQxygIyIiIiIiIiIikiEucSUiIiIiIiIiokITcY1rgXEGHRERERERERERkQxxgI6IiIiIiIiIiEiGuMSViIiIiIiIiIgKTcTnuBYYZ9ARERERERERERHJEAfoiIiIiIiIiIiIZIhLXImIiIiIiIiIqND4FNeC4ww6IiIiIiIiIiIiGeIAHRERERERERERkQxxgI6IiIiIiIiIiEiGOEBHREREREREREQkQxygIyIiIiIiIiIikiEO0BEREREREREREcmQoqwbQEREREREREREvz6RSNYt+HVxBh0REREREREREZEMcYDuJzNw4ECIRCKIRCIoKSnBwMAAzZo1w4YNG5CZmSkpZ2JiIimnpqYGExMTdO/eHefOnfvua0ZGRmL48OEwMjKCiooKDA0N0aJFC1y9ejVf55uYmGDJkiVS++7evYtu3brBwMAAqqqqMDMzw9ChQxEQEAAACA0NhUgkglgsxqtXr6TODQ8Ph6KiIkQiEUJDQ6XKf9p0dXXRvHlz3L1797vzfo+d27ehVbPGqGFXBX16dsPDBw++Wv70qRPo0LYlathVQZeO7XD50kWp44IgYMXypWjSsB5q2ttg2JCBCAsLlRxPTU3F5EkT4FDTHu1at8CN69ekzvfe4AWPWTOKLF9emJu5v4a5c8995r/T+GvoYDRwqIWq1hbw9/PLUcf8uR6oX6cmmjdpiGNHD+eo33HE34UP9g3sb+b+GuZm7s8xN3Mz9++be9WK5ejQtiVqVbdFvTo1MGzIQDx4cF9yXBa5NdRVMH98Fzw9Ph3vri/Cee+xqGZlJDleUkcTa937Ivj0LERfW4RDniNQ0Uj/q3UqKirAeVhLPD7shpgbi+GzaxKaOVjmKFdaXwsbZvbHy/Nz8e76ItzcPRn2n117TL8mCDvrgbCzHhjdr7HUuTUqG+PqtokQizm8QoUk0E9lwIABQsuWLYXw8HDh5cuXwu3bt4VZs2YJGhoaQqtWrYS0tDRBEATB2NhYmD59uhAeHi6EhYUJFy9eFIYOHSqIRCJh5syZ33XN+vXrC7Vq1RLOnTsnhIaGCj4+PsLs2bOFQ4cO5et8Y2NjYfHixZLXR44cEZSVlYV27doJ//33nxAcHCzcuHFDGDdunNC9e3dBEAQhJCREACCUK1dOmD17tlR9Hh4egpGRkQBACAkJkSp/5swZITw8XLh586ZQp04dwcDAQIiJicl31qS0/G8HDh8TrK2thR279wqP/AIF58kuQrXq1YWXEVG5lr/ue1uwtLQUVq1ZJzz2fybMX7hYsLKyFh48eSops2LVGqFatWrC8VP/Cfcf+QnD/vpbaNS4sRCbkCwkpQnCeu/NQsuWrYSHfgHC6rVeQq3atYXE1EwhKU0QAkOeC02bNRciY95/V47v3ZibuZm7YLl37zsgLF66XNi2Y7dgbm4u3H3wRKqOE6fPCnXqOAi37j4Q9h88IlSpUkV4/TZaSEoThLfv4oWmzZoLwWGvfrnc8trfzM3czM3czM3cv3LufQcOC+cvXRUCg58LD/0CBCfnyYK9vb3w6k30D82tajsyz23PyVvC42evhSaDFwlW7dyEGauOCbHxiUKFZpMFVduRwo37wcLl24FC3d5zhSod3IV1ey4LYa+jBZ3a/+ZZ54INp4VXb2KEDqNWCJXaTBUcZ+0QEpNShFo9PCRlDOuPF0JfRQmbDl4X6vWZJ1i0niq0+Xu5YNnWTVC1HSlU7zZL+JCYIrQYulRoOWypkJiUIlTrOktQtR0pFKvmKNz1ey7U7T33q9nkSWxixk+5/Qo4QPeTGTBggNChQ4cc+8+ePSsAENatWycIQs5BsU+mTp0qKCgoCP7+/pJ9Fy5cEGrUqCEoKysLhoaGgpOTk2SgLyYmRgAgXLhwocBt/rwtHz58EPT09ISOHTvmWvbTYNqnATcXFxfBzMxMqoy5ubng6uqa6wDd3bt3JeWuXr0qABBOnjyZ77Z+zw+Pzl26Cq5u7pLXH1IyhLr16gmeK9fkWn7UP6OFIUOHSe3r0rWbMNnFVUhKE4TE1EzBwaGusHqtl+T423fxQuXKlYX9h44KSWmC4OLqJnjMnS8kpQlCzPskwdzcXPJDcuCgwcLRE6d/6A9/5mZu5i5Y7s+3Z6Evch2gW7l6reA4eozkde06dYSbd+4LSWmC4DzFVVjrtfGXyy2v/c3czM3czM3czP0r585ti4x5L5ibmwsXLl/7obnzGsAqUWuMkJaWLnQctVJq/+3HYYLH2hNC5fbugiAIgl3nGZJjanajhDfR8cLf7lvzrPf121hh9OxdUvsOnLkrbD/qI3k9f8Mp4crtwDzr6DPBS/C5Hyx57fsgROg93ktQtR0puCw7JHhuO/fVwTkO0P0c26+AczB/EY0bN0bVqlWxf//+r5YbPXo0BEHAoUOHAACvXr1C69atUaNGDdy/fx+rVq3C+vXrMXPmTACAhoYGNDQ0cPDgQaSkpBS6nadOnUJUVBQmTpyY6/ESJUpIvW7fvj1iYmJw5coVAMCVK1cQExODdu3affNaampqALKmXxe1tNRU+D15jNp1HCT7FBQUULu2Ax7cz31Z7YN791C7dh2pfQ516+HBvXsAgFcvXyIqKhK1amfXqampiSo2VSV1mleqhLt3biM5ORnXrl6Bvr4+tLW1cezoYaioqKBJ02ZFnFQaczM3cxcsd36YW1TCk0ePEB8XhyePHyElORlGRsa4c/sW/J88Ru++/QqUJ7/Y38zN3Mz9OebOxtzMLW+5c7vGvj27oKmpCXMLCwD//9yKYgUoKoqRnJomtT85JQ0OdhWhopz1fMvk1HTJMUEQkJqaDgfbinnWq6ykmKPOpORUONhln9OmYRXcefIc2+YNRthZD1zf4YRBnbLf70fPXsPUuCTKGWrDqJQ2TI1L4nHQa5Qvq4f+7Wtj2oqjhcpO9Amf4voLqVSpEh58414DOjo6KFmypOTebStXrkS5cuXg6ekJkUiESpUq4fXr13BycsLUqVOhqKgIb29vDB06FKtXr4a9vT0aNmyInj17wsbG5rvbGBgYKGlrfigpKaFv377YsGED6tWrhw0bNqBv375QUlL66nmxsbGYMWMGNDQ0ULNmzVzLpKSk5Bh0FMQqUFFR+Wa7YmJjkJGRAV1dXan9urq6CAkJzvWcqKgo6Orq5SgfFR318Xhk1j69nHVGRWWV6dipCwKfPkWn9q2hXUIb8xYuQXxcHFZ6LsP6jVvguXQxTp44jrLljOA+czYMDAy+meV7MDdzf2ojc0v7Vu78qFuvPtq0a4/ePbpCRVUVM2bPhZqaGmbNcMeMWR7YvXMHdmzfAu0S2nB1nwFTU7PvD/cV7G/m/tRG5pbG3F9kYu6sfcydXYa5f7vcn1y8cB5O48ciOTkJevr6WL1uA7S1dQD8/3MnJKbgxv1gOA9thachb/AmOh7dW1ZHLZvyCHoRiaehEXge/g4zHNtj1Mwd+JCUin/6NkJZQ20Y6mnlWe+Z6374p29jXLnzDMEvotCopgU6NLaFWJz9qNHyZfQwtFt9LNt6DvPWn0Y1a2MsnNgVqekZ2HbEB09D3sDN8wiOrhoFAJi6/DCehrzBsdWjMGXJQTRzsMSUv1ojLT0D4+fvxdU7QYV6L351fIprwXGA7hciCAJE+fhq/7ycn58f6tSpI3Ve3bp1kZCQgJcvX8LIyAhdunRBmzZtcPnyZdy4cQMnTpzAvHnz4OXlhYEDB353G7/X4MGD4eDggNmzZ2PPnj24fv060tPTcy3r4OAABQUFfPjwARUqVMCuXbvy/GHg4eEBd3d3qX1TXN3gMnXad7fx/0VJSQmTXd2k9rlOcUbvPv3g7/cE586dxe79h+C9wQtzZ8/EoqXLZdTSosXc2Zj7980NAMNHOmL4SEfJ69UrPVG7dh0oKipi3ZpV2HvwCC5dPA8XZyfs3PP1GdO/Cnntb+bOxtzMzdzM/Sv7nXPXqFkLu/cdRGxsDPbt3Y0J48Zg64490NXVlUnuwS6bsWZaHwSfnoX09Azc83+B3Sdvwc7SCOnpmeg5bh1WufVB+KX5SE/PwDmfpzh55fFXB4TGz9+Lla69cH+/KwRBQPDLKGw+fAMDOtSWlFFQEOHOk+dw8zwCALj/9CWsTUthaNd62HbEBwDgtfcKvPZekZzTp10tJHxIgc+DENw/6Ip6feejTMkS2DJnMCq1cUNqWu5/zxJ9DZe4/kL8/PxQvnz5r5aJjo5GZGTkN8t9SVVVFc2aNYOrqyuuXbuGgQMHws3N7dsnfsHc3BwA4O/vn+9zqlSpgkqVKqFXr16wtLRE5cqV8yy7a9cu3L9/HzExMQgKCkLr1q3zLOvs7Iy4uDipbYKTc77apF1CG2KxGNHR0VL7o6Ojoaenl+s5enp6iP7iU6n/tXfncTWm/R/AP+e074tkSREVoZJ9z/bYZXuGsZU09m3GlrEl+zB2xq6yjJ3sa8gSWaKyJCXKFiJUkur8/vDrPI4KMzrn1n0+79fLa6b7vtXnKqdzn++5ru+VnJwMi/9/98rC4uMOQ8kvvv1zXgq7iLjYu/i5Z29cvnwJjRo1hr6+Plq2boMrly9901j+CY6b4/5aRo77s+uL5X/9t4i/F4eD+/dh6PCRuHz5EmrUrAlzc3O0bNUGt2/dRFpa6r/+3Pnhz5vj/lpGjvuz6znuj8c47q9+To6b4y5q486lr68Pm7Jl4exSDX7TZ0FTQxNBu3fm+zlVMe74hy/Q8pfFKFZvFOzbTEajPn9CS1MD8Y8+juXa7UTU/XkOSjQaA9uWE9Fx2F8oZmKA+IfJBX7OF69S0W3UGhSrPwoV206BS+fpSEt/j/hH//s7T1+8we17TxX+XnT8U1iXNMv3cxYzNcDEAW0w6o8dqOVUDrEPniEu4TnOXLkLTU0p7MtaFsJ3g9QRC3RFxMmTJxEVFYWuXbt+8brFixdDKpWiU6dOAABHR0dcuHBBYWbb+fPnYWRkhDJlyhT4eSpXroy0tLR/nLNly5awsLDA3Llz8z2fkpKS7/F+/frh9OnT6Nev3xc/v7W1NSpUqJCnl11+dHR0YGxsrPDnW5a3AoCWtjYcK1dB2MUL8mM5OTkIC7sAZxfXfP+Oc7VqCLt4UeHYxQuhcK5WDQBgVaYMLCyKIyzsf58zNTUVUZER+X7O9+/fY/aMaZg8dRo0NDSQk5Mtn1mY9SELOTnZ3zSWf4Lj5rg57n837n9KJpNhup8vRo8bD30DA+Rk5+BD7rj//7/Z2Tn/6nMXhD9vjpvj5rg/xXH/D8fNcavbuAuSI8vJt7+3qsednpGJpy/ewNRIDy3qO+LA6SiF829SM/DiVSoq2BRH9co2OHD6y22gAOB9ZhYeP38NTU0pOjWvpvB3Lly/B4fPimr2NpZIePIy3881d3RXLN18Co+epUBDKoGmpob8nKaGBjSk6r3GU/KD/ikKWKD7Ab1//x5Pnz7Fo0ePEB4ejlmzZqFjx45o3749PDw85Ne9ffsWT58+RWJiIs6cOYMBAwZgxowZmDlzJuzs7AAAQ4YMQWJiIoYPH47o6Gjs3bsXvr6+GDVqFKRSKZKTk9GsWTNs2rQJkZGRiI+Px44dOzB37lx07NjxH2c3MDDA2rVrcfDgQbi7u+PEiRO4f/8+rly5gnHjxmHQoEH5/r3+/fvj+fPn+OWXX/7dN00J+nh6YffO7dgXtAf34uIwY9pUvHv3Dp06dwEATPx9HBYvnC+/vldvD4SeP4vAgPWIvxeHFcuX4uaNG/i5Z28AgEQiQa8+HlizagVOnwzG3Zg7mPT7OBS3tESz5i3yfP3VK/9Cw8ZucHSsDACo5lodwSeOI+ZONLZu2YRqrtU5bo6b4/5Bxg0Ar1NSEH37Nu7Ffew7cv9+PKJv38aL58/zfP3dO3fAzMwcTZo2k4/7cthFREZcx6YNAShfwQ7GxsY//LjV9efNcXPcHDfHzXFz3EV53Onp6ViyaAEiI67j8eNHuHXzBqZM+h3PkpLwn1atBRt3i3qO+E99R5QtXQzN6lTCkTUjEROfhA37PhYnu7RwRaMa9ihnVQztmzjh4Iph2H86EsEX/7d6a+30Ppg23F3+ca2qZdGxmQvKWRVDA9cK2LdsKKRSCRYEnJBfs3TTSdR2ssXYfi1R3toC3VvXRL+uDbBq25k8GZvVqQT7spZY+f/nrt5MQMVyJdCyQWX069IA2dk5iHnwrFC+H6R+2IPuB3TkyBGUKlUKmpqaMDMzg4uLC5YsWQJPT09Ipf+rqU6ZMgVTpkyBtrY2SpYsibp16yI4OBhNmzaVX2NlZYVDhw5h7NixcHFxgbm5Oby9vTFp0iQAH3dxrVOnDhYuXIi4uDh8+PAB1tbW6N+/PyZMmPCv8nfs2BGhoaGYPXs2evbsiTdv3sDa2hrNmjWT7x77OU1NzQKnaAuldZu2ePXyJf5atgQvXjxHxUqO+GvVWhT7/5xPnzyBVPK/n0c11+qYPfdPLFuyCEsXLYBN2XJYtHQ57O0d5Nd4effHu3fvMG3qFLx9+wau1Wvgr1Vr88zsu3s3BseOHMa2XUHyY/9p2RpXLl2Cl0cvlC1nizlz50MZOG6Om+P+d+M+feokpkz63zJ6nzG/AQAGDRmm0Hcu+cULrF29EoGbt8iPOTk7o4+nF4YNHgjzYuaYPvOPIjNudf15c9wcN8fNcXPcHHdRHbeGhgbi4+9h3949SHn1CqampqhS1Qn+Gzbn2aRKleM2MdTFtOHusCphipev07E3+Dp8l+9HVtbHVQUlixvjj9FdYFnMCE9fvMHmA2GYvfqIwuewLmmOnJz/rR7T0dGC79D2sLWyQGr6exw9fxPekzfgdeo7+TVXbyWg++g1mDbcHRMGtMH9R8kYO28Xth6+ovC5dXW0sHD8T+jjs16+Qu3RsxSMmrsDq6b2RuaHLPSfshEZ7xV3jSX6VhLZv+nqT1REZbBXJxERERERkSDMag0TOoIg3l1bJnQElXn7vnDbtBQWI50ffwHpj5+QiIiIiIiIiIhIxFigoy/avHkzDA0N8/1TpUoVoeMRERERERERERV57EFHX+Tu7o46derke05LS0vFaYiIiIiIiIjoRyUpMnum/nhYoKMvMjIygpGRkdAxiIiIiIiIiIhEi0tciYiIiIiIiIiIBMQZdERERERERERE9N0kXOH6r3EGHRERERERERERkYBYoCMiIiIiIiIiIhIQl7gSEREREREREdF34wrXf48z6IiIiIiIiIiIiATEAh0REREREREREZGAuMSViIiIiIiIiIi+H9e4/mucQUdERERERERERCQgFuiIiIiIiIiIiIgExCWuRERERERERET03SRc4/qvcQYdERERERERERGRgFigIyIiIiIiIiIi+sTy5ctRrlw56Orqok6dOrh06dIXr9+xYwcqVaoEXV1dODk54dChQ//o67FAR0RERERERERE300i+TH//FPbtm3DqFGj4Ovri/DwcLi4uKBVq1Z49uxZvteHhoaiR48e8Pb2xrVr19CpUyd06tQJN27c+PbvnUwmk/3zqERFU0aW0AmIiIiIiIjUk1mtYUJHEMS7a8uEjqAyP+prbt1/uANDnTp1UKtWLSxb9vFnl5OTA2trawwfPhzjx4/Pc3337t2RlpaGAwcOyI/VrVsX1apVw8qVK7/pa3IGHRERERERERERidb79+/x5s0bhT/v37/P99rMzExcvXoVLVq0kB+TSqVo0aIFLly4kO/fuXDhgsL1ANCqVasCr8+XjIiULiMjQ+br6yvLyMgQOopKcdwctzrguDludcBxc9zqgOPmuNUBx61e46b/8fX1lQFQ+OPr65vvtY8ePZIBkIWGhiocHzt2rKx27dr5/h0tLS3Z33//rXBs+fLlMktLy2/OyCWuRCrw5s0bmJiY4PXr1zA2NhY6jspw3By3OuC4OW51wHFz3OqA4+a41QHHrV7jpv95//59nhlzOjo60NHRyXPt48ePYWVlhdDQUNSrV09+fNy4cQgJCUFYWFiev6OtrY3AwED06NFDfuyvv/6Cn58fkpKSvinjP1yFS0REREREREREVHQUVIzLj4WFBTQ0NPIU1pKSklCyZMl8/07JkiX/0fX5YQ86IiIiIiIiIiIifJwNV6NGDQQHB8uP5eTkIDg4WGFG3afq1auncD0AHD9+vMDr88MZdERERERERERERP9v1KhR8PT0RM2aNVG7dm0sWrQIaWlp8PLyAgB4eHjAysoKs2fPBgCMHDkSbm5umD9/Ptq1a4etW7fiypUrWL169Td/TRboiFRAR0cHvr6+3zylViw4bo5bHXDcHLc64Lg5bnXAcXPc6oDjVq9x07/XvXt3PH/+HFOmTMHTp09RrVo1HDlyBCVKlAAAJCQkQCr936LU+vXr4++//8akSZMwYcIE2NvbIygoCFWrVv3mr8lNIoiIiIiIiIiIiATEHnREREREREREREQCYoGOiIiIiIiIiIhIQCzQERERERERERERCYgFOiIiIiIiIiIiIgGxQEdEREREpMZkMhkSEhKQkZEhdBQiIiK1xQIdEREREZEak8lksLOzQ2JiotBRSCAPHjzArVu3kJOTI3QUIiK1pSl0ACKxefPmzTdfa2xsrMQkpGoF/ewlEgl0dHSgra2t4kSqlZmZifj4eFSoUAGamuJ/egkODkZwcDCePXuW5wXN+vXrBUqlXNu2bcO+ffuQmZmJ5s2bY9CgQUJHUpn3798jKysLBgYGQkchKnRSqRT29vZITk6Gvb290HFU6sOHDxg4cCAmT54MW1tboeMo3fr165GSkoJRo0bJjw0YMADr1q0DAFSsWBFHjx6FtbW1UBFJCe7fv4/jx48jMzMTbm5uqFq1qtCRVOLNmzcICwtDZmYmateujeLFiwsdieiLJDKZTCZ0CCIxkUqlkEgkX7xGJpNBIpEgOztbRalUIyEh4Zuus7GxUXISYXztZ1+mTBn07dsXvr6+kErFM4E5PT0dw4cPR2BgIAAgJiYG5cuXx/Dhw2FlZYXx48cLnLDw+fn5Ydq0aahZsyZKlSqV5+e+Z88egZIpz4oVKzB06FDY29tDT08PUVFRGDVqFObNmyd0NKV6/vw5PDw8cOLECeTk5KBWrVrYtGkT7OzshI6mNJ++cP+aBQsWKDGJcPbt25fvcYlEAl1dXdjZ2YmumLN//37MnTsXK1asUJsX77lMTExw/fp10f1M81O3bl0MHDgQXl5eAIAjR46gQ4cOCAgIgKOjI4YNG4bKlStj7dq1AidVns6dO+d7v/bp47tnz56oWLGiAOkK36lTp9C+fXu8e/cOAKCpqYn169ejd+/eAidTruvXr6Nt27ZISkqCTCaDkZERtm/fjlatWgkdjahALNARFbKQkJBvvtbNzU2JSVRPQ0ND/v+5v1o+vQESa2Ey14YNGzBx4kT07dsXtWvXBgBcunQJgYGBmDRpEp4/f44///wTY8eOxYQJEwROW3hGjhyJ8+fPY9GiRWjdujUiIyNRvnx57N27F1OnTsW1a9eEjljoSpUqhblz56JPnz5CR1GZKlWqoFu3bvD19QUAbNq0CQMHDkRaWprAyZSrX79+OHz4MEaMGAFdXV2sWrUKpUqVwqlTp4SOpjRNmzZV+Dg8PBxZWVnyF6sxMTHQ0NBAjRo1cPLkSSEiKl3uGy6f3ybnHpNIJGjYsCGCgoJgZmYmUMrCZWZmhvT0dGRlZUFbWxt6enoK51++fClQMuXz9PREtWrV8NtvvwkdRemKFSuG06dPw8nJCQAwePBgPH/+HDt37gQAnD59Gl5eXoiPjxcyplL17dsXQUFBMDU1RY0aNQB8/D2XkpKCli1bIiIiAvfv30dwcDAaNGggcNrv17BhQ1hYWGDFihXQ1dXFpEmTsGfPHjx+/FjoaErVqlUrpKam4s8//4Suri6mT5+OqKgo3L17V+hoRAVigY6ICo2mpqZ8lliHDh0KXObo4uKi4mSq0bx5cwwcOBDdunVTOL59+3asWrUKwcHB2LhxI2bOnIno6GiBUha+smXLYtu2bahbty6MjIwQERGB8uXLIzY2FtWrV/9Hy76LimLFiuHSpUuoUKGC0FFURk9PD7dv30a5cuUAADk5OdDT08P9+/dRqlQpYcMpkbW1NdauXSt/x/3u3btwdHREWloadHR0BE6nfAsWLMDp06cRGBgoL0S9evUKXl5eaNSoEUaPHi1wQuUIDg7GxIkTMXPmTIU3XCZPnoxJkybBxMQEAwcORJ06deRLA4u63FnQBfH09FRREtWbMWMG5s+fj+bNm6NGjRp5lrKPGDFCoGSFT19fH7dv30bZsmUBfLwn8/b2lo8xISEBFStWlM+2EqPx48fjzZs3WLZsmXxFQ05ODkaOHAkjIyPMnDkTgwYNws2bN3Hu3DmB034/U1NThIaGonLlygA+rnwwNjZGUlISihUrJnA65bGwsMCxY8dQvXp1AEBKSgrMzc2RkpLCNkP0w2KBjkgF0tPTkZCQgMzMTIXjzs7OAiVSjqdPnyIwMBD+/v5ISUlB79694e3tDUdHR6GjqYSenh4iIyPz9O+5e/cuXFxckJ6ejvj4eFSpUgXp6ekCpSx8+vr6uHHjBsqXL69QoIuIiEDjxo3x+vVroSMWOh8fHxgaGmLy5MlCR1EZqVSKpKQkhf4tn/68xUpDQwOPHj1CyZIl5ccMDAxw8+ZNebFSzKysrHDs2DFUqVJF4fiNGzfQsmVL0c7AqFq1KlavXo369esrHD9//jwGDBiAmzdv4sSJE+jXr983t3egH9eXlrZKJBLcu3dPhWmUy9HRETNnzkSXLl3w4sULlCxZEmFhYfKZZJcuXYK7uzuePn0qcFLlKV68OM6fPw8HBweF4zExMahfvz5evHiBqKgoNGrUCCkpKcKELERSqRRPnz6FpaWl/Jg6PH8XNO7IyEi1WM5ORZP4u3gTCej58+fw8vLC4cOH8z0vtqWeJUuWhI+PD3x8fHDu3Dn4+/ujTp06qFy5Mry9veHt7S2q3mufs7a2xrp16zBnzhyF4+vWrZM3W05OThbNcqhcNWvWxMGDBzF8+HAA/1vWvHbtWtSrV0/IaEqTkZGB1atX48SJE3B2doaWlpbCebH25Zo8eTL09fXlH2dmZmLmzJkwMTGRHxPj2D9dvp/7sbq8v/nmzRs8f/48z/Hnz5/j7du3AiRSjbi4uHxnWBgbG8uLNfb29njx4oWqoylVXFwc/P39ERcXh8WLF8PS0hKHDx+GjY1NniKtmIh5OefnPD09MXToUNy8eRMnT55EpUqV5MU5AAgNDRV9D8KsrCxER0fnKdBFR0fL7811dXW/2lO6KDl69KjCc3VOTg6Cg4Nx48YN+TF3d3choinVrVu3FIrNMpkMt2/fVnj+EtuECSraWKAjUqJff/0VKSkpCAsLQ5MmTbBnzx4kJSXJl1KIWcOGDdGwYUPMmjULPXr0wKBBg9C1a1eYm5sLHU1p/vzzT/z00084fPgwatWqBQC4cuUKoqOj5b1dLl++jO7duwsZs9DNmjULbdq0wa1bt5CVlYXFixfj1q1bCA0N/Uc9GYuSyMhIVKtWDQAUbm4BiOqG/lONGzfGnTt3FI7Vr19fYWaJGMcuk8ng4OCgMLbU1FS4uroqvOEg1v5cnTt3hpeXF+bPny9f6hkWFoaxY8eiS5cuAqdTnho1amDs2LHYsGGDfNbo8+fPMW7cOPnv97t374pqp8uQkBC0adMGDRo0wJkzZzBz5kxYWloiIiIC69atkz+PiV1+PXTFZNy4cUhPT8fu3btRsmRJ7NixQ+H8+fPn0aNHD4HSqUafPn3g7e2NCRMmyB/Ply9fxqxZs+Dh4QHg4+NBTEXp/JaoDxw4UP7/Yu0R3bx58zxvqLVv316hn6gYx01FF5e4EilRqVKlsHfvXtSuXRvGxsa4cuUKHBwcsG/fPsydO1cUfS0KEhoaivXr12PHjh2oWLEi+vXrhwEDBoh6Bh3w8V34VatWISYmBgBQsWJFDBw4UPRL4e7du4fZs2cjIiICqampqF69Onx8fORNqImKqq/15col1v5c6enpGDNmDNavX48PHz4A+Nhv1NvbG/PmzcvTq0ss7ty5g44dOyI+Pl5ehEtMTJRvgOPg4ICgoCC8fftWNJvF1KtXDz/99BNGjRqlsPzt0qVL6NKlCx4+fCh0RKXasGED5s2bJ28g7+DggLFjx4rm50v/k52djTlz5mDZsmVISkoCAJQoUQLDhw+Hj48PNDQ0kJCQAKlUijJlygiclv6tBw8efNN1uf0YiX4ELNARKZGxsTEiIyNRrlw5lC1bFn///TcaNGggyj5kAPDkyRNs2LAB/v7+ePXqFXr16oV+/fqJfqmEOvvw4QMGDhyIyZMnq20/j9wXrWK/iS9fvjwuX74s6obSpCg7Oxvnz5+Hk5MTtLW1ERcXBwCoUKGCaAtzn8rJycGxY8cU3nD5z3/+I9o3mgwNDREVFQVbW1uFAt39+/dRqVIlZGRkCB1RaRYsWIDJkydj2LBh8l07z507h+XLl2PGjBmi3901IyMD27ZtQ1paGlq2bAk7OzuhI6lM7kZW3DSAiH4ELNARKVGtWrUwY8YMtGrVCu7u7jA1NcXs2bOxZMkS7Ny5U/5iRyy0tLRgZWUFT09PuLu75+nLlUvMvR5SUlJw6dIlPHv2DDk5OQrncpdNiI2JiQmuX7+uVgW6nJwc+VL11NRUAB8bD48ePRoTJ04U5Qv4/Jotq4NXr15h06ZN8PT0zPMC7vXr19iwYUO+58RCV1cXt2/fVqvHt7oqU6YMtm/fjvr16ysU6Pbs2YMxY8aI7p7lU7a2tvDz88vzPB0YGIipU6eKqkfdqFGj8OHDByxduhTAx16iderUwc2bN6Gvr4+srCwcP35ctD1k1dnJkyexe/du3L9/HxKJBLa2tvjvf/+Lxo0bCx1NKb51Ax8bGxslJyH6dizQESnRpk2bkJWVhb59++Lq1ato3bo1Xr58CW1tbQQEBIiuF9mnRYnc3i2f/4oRc6+H/fv3o1evXkhNTYWxsbFC/xqJRCLaHlWenp6oVq2a6GcYfOr333/HunXr4OfnpzDbYurUqejfvz9mzpwpcMLCp64FuunTpyMyMjJPn6Zc3bp1g4uLCyZOnKjiZKpRs2ZN/PHHH2jevLnQUVQuODgYwcHB+b7hsn79eoFSKc+YMWMQFhaGHTt2wMHBAeHh4UhKSoKHhwc8PDzg6+srdESl0dXVxY0bN/LMHLt79y6cnJxENXuwatWqmDVrlnxDAH9/f4wePRrXrl2DjY0N+vXrh2fPnuHgwYMCJ1WepKQkjBkzRv74/vxeVYz3qYMGDcLq1athZmYGBwcHyGQy3L17FykpKRgyZIi8YCsmn27wlF9vSfagox8RC3REKpSeno7o6GjY2NjAwsJC6DiFTt17PTg4OKBt27aYNWuWwk6XYpc7k6x58+aoUaNGnqVvI0aMECiZ8pQuXRorV67Ms+PZ3r17MWTIEDx69EigZMojlUoRGBiosAtcfsS2C1y1atXk/77zExwcjDFjxuDatWsqTqYaR44cwe+//47p06fn+/gW68xBPz8/TJs2DTVr1kSpUqXybBiwZ88egZIpT2ZmJoYOHYqAgABkZ2dDU1MT2dnZ6NmzJwICAvLsZiwmVatWRc+ePTFhwgSF4zNmzMC2bdsQFRUlULLCZ2xsjPDwcHkxskePHjAyMsLq1asBANevX0fbtm3x+PFjIWMqVZs2bZCQkIBhw4bl+/ju2LGjQMmUY8+ePfj555+xatUqeHp6ysebk5ODgIAADB48GDt27BDd87empibKlCmDvn37okOHDtDUzH9/TBcXFxUnIyoYC3REVGimTZuGMWPGqFVx6lMGBgaIiopC+fLlhY6iUl9a+iaRSBR2+RQLXV1dREZGwsHBQeH4nTt3UK1aNbx7906gZMrzLct2xfhOtJGREW7evFngEpiEhARUrVpV3sdIbPKbGQ2If+ZBqVKlMHfuXLXcICAhIQE3btyQ71Zsb28vdCSl27VrF7p3744WLVrIZ0WfP38ewcHB2L59Ozp37ixwwsJjamqKy5cvy3+utra2mDx5Mvr16wcAuH//PhwdHUX5PJbLyMgIZ8+ele/GLnbu7u6oUqUKZs+ene95Hx8fREdHY+/evSpOplxPnz5FYGAg/P39kZKSgt69e8Pb2xuOjo5CRyMqUP5lZCIqFDKZDDt37sSpU6fyXSKze/dugZIph5+fHwYNGqS2BbpWrVrhypUralegE1Nvnm/l4uKCZcuWYcmSJQrHly1bJup3YtVxiauGhgYeP35cYIHu8ePHouw5mOvUqVNCRxBEZmYm6tevL3QMQdjY2KhdT6auXbsiLCwMCxcuRFBQEADA0dERly5dgqurq7DhCpmjoyP279+PUaNG4ebNm0hISEDTpk3l5x88eIASJUoImFD5rK2t8yxrFbPw8HBMmjSpwPNdunRB165dVZhINUqWLAkfHx/4+Pjg3Llz8Pf3R506dVC5cmV4e3vD29tb1M/fVDRxBh2REo0cORKrVq1C06ZNUaJEiTxT6P39/QVKphzq2qMq17p16zBt2jR4eXnByckpzyYZYls6oM5CQkLQrl072NjYyBtpX7hwAYmJiTh06BAaNWokcMLCp6GhgSdPnqjd47tp06aoU6cO5syZk+95Hx8fXLp0SW0LWWLl4+MDQ0NDTJ48WegoKpOdnY2AgIAC++6dPHlSoGRUmHKXOzZs2BA3b95ErVq1sH//fvl5Hx8f3Lt3r8C+m2Jw7NgxzJ8/H6tWrUK5cuWEjqN0urq6uHfvHkqXLp3v+UePHsHOzk7UsyZzJSUloUePHggJCcHz589hbm4udCQiBZxBR6REGzduxO7du9G2bVuho6jM50VIddK/f38AH5f6fk7MS8EA4OHDh9i3bx8SEhKQmZmpcG7BggUCpVIeNzc3xMTEYPny5YiOjgbw8R3oIUOGFHgDXNSp6/t5w4YNw88//4wyZcpg8ODB8j5c2dnZ+Ouvv7Bw4UL8/fffAqdUrpSUFKxbtw63b98GAFSpUgX9+vX7aj/CoiwjIwOrV6/GiRMn4OzsnOcNFzH+Xhs5ciQCAgLQrl07VK1aVe2ez7OzsxEUFKTw79zd3V10vfc6d+6MQ4cO4cCBA2jZsiWGDx+ucF5fXx/Dhg0TKJ1qdO/eHenp6ahQoQL09fXzPL7FtqlXZmZmnjF+SlNTM8+9m9iEhoZi/fr12LFjBypWrIjly5fD1NRU6FhEeXAGHZES2dra4vDhw6hUqZLQUVRCKpXCxMTkqzf1YrvxUXfBwcFwd3dH+fLlER0djapVq+L+/fuQyWSoXr06Z12IhJeXF5YsWQIjIyOho6jcxIkTMXv2bBgZGcmXsN+7dw+pqakYO3ZsgbPrxODKlSto1aoV9PT0ULt2bQDA5cuX8e7dOxw7dgzVq1cXOKFyfLrk73MSiUSUv9csLCywYcMGtXpTMVdsbCzatWuHhw8fomLFigA+9hS1trbGwYMHUaFCBYETFp7JkyfD19e3wIb5Dx48wC+//ILjx4+rOJnqBAYGfvG8p6enipKohlQqxYABAwpsQZOeno41a9aI7o3kJ0+eYMOGDfD398erV6/Qq1cv9OvXD1WrVhU6GlGBWKAjUqLAwEAcOXIE69evh56entBxlE4qlWLRokVfnVUhthsfdVe7dm20adMGfn5+MDIyQkREBCwtLdGrVy+0bt0agwcPFjpioYiMjETVqlUhlUoRGRn5xWudnZ1VlEp11HWJ65kzZ1CvXj1cu3YNmzdvRmxsLGQyGRwcHNCzZ0950UqsGjVqBDs7O6xZs0b+gj4rKwu//PIL7t27hzNnzgickApL6dKlcfr06Tyb36iDtm3bQiaTYfPmzfIlb8nJyejduzekUikOHjwocMLCY2NjIy/Gfl6oWLVqFcaNG4f69evj8OHDAiWkwtakSZNvmhErtlYNWlpasLKygqenJ9zd3QucRSjGezYquligI1Kid+/eoXPnzjh//jzKlSuX54khPDxcoGTKoY496JYsWYIBAwZAV1c3z4YBnxsxYoSKUqmWkZERrl+/jgoVKsDMzAznzp1DlSpVEBERgY4dO+L+/ftCRywUn/77lkqlkEgk+S77FOtyZnV8fAPqW5jMpaenh2vXruWZCX7r1i3UrFkT6enpAiWjwjZ//nzcu3cPy5YtU7vlrQYGBrh48SKcnJwUjkdERKBBgwZITU0VKFnhe/PmDYYNG4bt27fD19cXPj4+ePjwIfr164fLly9j3rx5GDBggNAxC92bN29gbGws//8vyb2Oirb8diH//L5NrPdsVHSxBx2REnl6euLq1avo3bt3vptEiI3Yx5efhQsXolevXtDV1cXChQsLvE4ikYi2QGdgYCDvXVKqVCnExcWhSpUqAIAXL14IGa1QxcfHo3jx4vL/V0dv376Frq7uF68R2wsbdX8f09jYGAkJCXkKdImJiaJb7tylSxcEBATA2NgYXbp0+eK1YtuFHQDOnTuHU6dO4fDhw6hSpUqeNxXFOOZcOjo6ePv2bZ7jqamp0NbWFiCR8hgbG2PDhg3o2rUrBg4ciG3btiE+Ph61a9dGZGQkypYtK3REpTAzM5O/2WJqaprvPatMJmPBRkTU9V6NijYW6IiU6ODBgzh69CgaNmwodBSVUMcXsp8++avrjUDdunVx7tw5ODo6om3bthg9ejSioqKwe/du1K1bV+h4hebTFy0PHjxA/fr18/TwycrKQmhoqGhf4Hxp6ZuYX9io45sPubp37w5vb2/8+eefqF+/PgDg/PnzGDt2LHr06CFwusL1aQ9VMW+AURBTU1N07txZ6BiCaN++PQYMGIB169bJl62HhYVh0KBBot2BvW7dunByckJwcDAMDAwwadIk0T53AR93Ic5dviy2pZxfU9AbDiYmJnBwcMAvv/wifwNSTMT875nEi0tciZSoUqVK2L59O3sbkKjlNst3dnZGWloaRo8ejdDQUNjb22PBggWivEEqaNljcnIyLC0tRVmkkkql2LVrl/wFTkHc3NxUlEg1pFIp2rRpAx0dnS9eJ9bZRZmZmRg7dixWrlyJrKwsAB/7+gwePBhz5sz56veFqChISUmBp6cn9u/fL585mJWVBXd3dwQEBIiuYLtlyxYMGzYM1apVw19//YV169Zh8eLFGDJkCGbPnv3VmdJFXUJCAqytrfO8+SKTyZCYmAgbGxuBkimHl5dXvsdTUlIQERGBlJQUnDlzRnSbJ9y9exdTpkzBqlWr8szuf/36NQYPHowZM2bIN38i+hGwQEekRAcPHsTSpUuxcuVKlCtXTug4Sve1JUG5xPRCdtSoUd987YIFC5SYhFRJKpUiKSkpzzvOMTExqFmz5lf72xRF6tqDTiqVolu3bl/d6Mff319FiYSRnp6OuLg4AECFChUK3A2QqCi7e/cuoqOjAQCOjo6ws7MTOFHh69q1K44ePYrZs2dj+PDh8uOhoaHyQk5AQADq1asnVESlU8c32QqSk5OD/v3749mzZ9i/f7/QcQrVgAEDYGpqirlz5+Z73sfHB2/evMGKFStUnIyoYFziSqREvXv3Rnp6uvzFzOf9XF6+fClQMuUwNjZWu6Vg165dU/g4PDwcWVlZqFixIoCPBRsNDQ3UqFFDiHgqMWXKFDRt2hT16tUT/bvuuUVoiUSCvn37Ksweys7ORmRkpHwZIInHkiVL1K4wmevkyZOoX78+9PX18zTQF7OkpCSMGTMGwcHBePbsWZ4WDmJ8Aa+OY/6cvb097O3thY6hVE+fPsW1a9fyjLN+/fq4fv06xo8fDzc3N3lvWTHKbcnwudTUVNHfx3xOKpVixIgRaNOmjdBRCl1ISAg2bdpU4Plu3bqhZ8+eKkxE9HUs0BEp0aJFi4SOoFIBAQFCR1C5T/uYLFiwAEZGRggMDISZmRkA4NWrV/Dy8kKjRo2Eiqh0Fy5cwIIFC5CVlYVatWrBzc0NTZo0QYMGDb4666ioyV3mJJPJYGRkpDA+bW1t1K1bF/379xcqnlKVLVsWGhoaQsdQOXV70+Fz7u7u8sd2kyZN4ObmJsrH9uf69u2LhIQETJ48GaVKlVKLfwfqNmZ1nQF/9uxZhd0tP6Wnp4fFixeja9euKk6lGrk/c4lEgsmTJyvMBM7OzkZYWBiqVasmUDrhGBgYiHJH7oSEhC++uWZhYYHExEQVJiL6OhboiJTkw4cPCAkJweTJk2Frayt0HJXo16/fV6+RSCRYt26dCtKo3vz583Hs2DF5cQ74uGvYjBkz0LJlS4wePVrAdMpz/PhxZGVlISwsDGfOnEFISAiWLFmC9+/fo1atWjh37pzQEQtN7jLGcuXKYezYsWq1zE9dN0FR904gr169wqVLlxASEoKQkBAsWrQImZmZqFmzJpo2bYoZM2YIHVEpzp07h7Nnz6rVi3V1G7O6zoAvqDj3qcaNG6sgierl/sxlMhmioqIUdujV1taGi4sLxowZI1Q8wRw/fvyLm0AVVSYmJoiLiyuwF3JsbKzodp6noo8FOiIl0dLSwq5duzB58mSho6hMQEAAypYtC1dXV7V8UfvmzRs8f/48z/Hnz5/j7du3AiRSHU1NTTRo0ADFixeHubk5jIyMEBQUJO/lIzYeHh549OhRniVCd+/ehZaWlih7TlavXv2brgsPD1dyEtU6derUVzfG+JSTkxMOHToEa2trJaZSHS0tLTRo0AANGjTAhAkTcPPmTcybNw+bN2/GxYsXRVugs7a2VrvnMXUbM2fAq5/cn7mXlxcWL16sNsWZffv25Xv89evXuHr1KtauXYu1a9eqOJXyNW7cGEuXLkWzZs3yPb9kyRI+vumHw00iiJTI09MT1apVw2+//SZ0FJUYOnQotmzZgrJly8LLywu9e/f+Ry9sizoPDw+cPXsW8+fPR+3atQEAYWFhGDt2LBo1aoTAwECBEyrH6tWrcfr0aYSEhOD9+/do1KgRmjRpgiZNmsDZ2VmUy6Tc3NzQr18/eHp6KhzftGkT1q5di9OnTwsTTIn8/Pzk/y+TyTB79mwMGjQoz2Pc19dX1dF+KEZGRoiIiBDNrnAxMTE4ffp0gY9xFxcXoSMqxbFjxzB//nysWrVKlAX3/KjjmHNZWVnh2LFjqFKlisLxGzduoGXLlnj8+LFAyYi+X0GzJo2MjFCxYkWMGjUKP//8s4pTKd+1a9dQr149tG/fHuPGjZPPjo2OjsbcuXNx8OBBhIaGfvMbkESqwAIdkRLNmDED8+fPR/PmzVGjRg0YGBgonB8xYoRAyZTn/fv32L17N9avX4/Q0FC0a9cO3t7eaNmypSgLNZ9KT0/HmDFjsH79enz48AHAx5ll3t7emDdvXp6fv1hIpVIUL14co0ePxpAhQ2BoaCh0JKUzNjZGeHh4nh3+YmNjUbNmTaSkpAgTTIXEVogqLGL7vuQ+vkeOHIn27dvDyclJ9L/LgY/tCdLT05GVlaUWmzwB6jnmXEZGRti/fz+aNGmicPzUqVNwd3cX/Sx4dZOWloY5c+bIN0TJyclROH/v3j2BklFhO3DgAPr164fk5GSF48WKFcPatWvh7u4uUDKi/LFAR6REX+o9J5FIRH8D8ODBAwQEBGDDhg3IysrCzZs31aJ4k5aWhri4OABAhQoVRFuYyxUUFIQzZ87g9OnTuH37NlxdXeWzaxo2bCjKPm0mJiY4ffo0XF1dFY5fvXoVTZo0UYsXc2IrRBUWsX1ffv31V5w5cwa3bt1C9erVRf/YzvW1Gc+fz54VA3Uccy51nQGvrnr06IGQkBD06dMn3w1RRo4cKVCyH4PYWjW8e/cOR44cQWxsLGQyGRwcHNCyZUtRP4dR0cUCHREpTWJiIvz9/REQEIDMzExER0erRYFOnb1+/Rpnz57Fjh07sGXLFkilUmRkZAgdq9B16NABenp62LJli3xn0+zsbHTv3h1paWk4fPiwwAmVT2yFqMIi1u9LSkoKzp49K98s4ubNm3B1dcX58+eFjkb03dR1Bry6MjU1xcGDB9GgQQOho/yQxPo8RlQUcJMIIhXJrYWLfWnQp0tcz507h/bt22PZsmVo3br1N+0cVtRduXIF27dvR0JCAjIzMxXO7d69W6BUypecnIyQkBB5r6qbN2/CzMxMtM13//jjDzRu3BgVK1aUj/Hs2bN48+YNTp48KXA6osKXnZ2NDx8+4P3798jIyMD79+9x584doWMpVU5ODmJjY/NdAifWXS5zZWRk5HkOE3NDfX19ffz111+YN2+eWs2AV1dmZmZq1SNZXS1ZsuSbrhNjyyEqujiDjkjJNmzYgHnz5uHu3bsAAAcHB4wdOxZ9+vQROFnhGzJkCLZu3Qpra2v069cPvXr1goWFhdCxVGbr1q3w8PBAq1atcOzYMbRs2RIxMTFISkpC586d4e/vL3REpXBycsLt27dhZmaGxo0bo0mTJnBzc4Ozs7PQ0ZTq8ePHWLZsGSIiIqCnpwdnZ2cMGzZMtDf9n9/o+vj4YOzYsXke4+p+oyu2mQcjRozA6dOncevWLflj3M3NDU2aNBF1P7qLFy+iZ8+eePDgQZ6dTSUSCbKzswVKpjxpaWnw8fHB9u3b8/RrAiDKMec6deoUmjZtmu+55cuXY+jQoSpORMq0adMm7N27F4GBgVzmmA+xPI99qdVQLnVoOURFCwt0REq0YMECTJ48GcOGDZNPoz937hyWL1+OGTNmiG53V6lUChsbG7i6un7xRZtYZ5I5Oztj4MCBGDp0qPzmxtbWFgMHDkSpUqUUdsEUk+XLl8PNzQ1Vq1YVOgopEW90v83ff/+Njh07imbmzU8//SQvyKnTY7xatWpwcHCAn59fvj2qTExMBEqmPEOHDsWpU6cwffp09OnTB8uXL8ejR4+watUqzJkzB7169RI6otKYmZnhxIkTqFGjhsLxxYsXY/LkyXjz5o1AyUgZXF1dERcXB5lMhnLlyuXZECU8PFygZD8GsRToiIoiFuiIlMjW1hZ+fn7w8PBQOB4YGIipU6ciPj5eoGTK0bdv32+aTSHWmWQGBga4efMmypUrh2LFiuH06dPy2WXNmjXDkydPhI5Ihejs2bNYtWoV7t27hx07dsDKygobN26Era0tGjZsKHQ8KiQXLlxAcnIy2rdvLz+2YcMG+Pr6Ii0tDZ06dcLSpUuho6MjYEoqbAYGBoiIiMizU7OY2djYYMOGDWjSpInCTtUbN27Eli1bcOjQIaEjKs3atWsxYcIEnDlzBpUqVQIAzJ8/H9OmTcOBAwdE265BXX3tDVNfX18VJfkxqWuBTmybY1DRxB50REr05MkT1K9fP8/x+vXri7JYExAQIHQEQZmZmcl377SyssKNGzfg5OSElJQUpKenC5xOeWQyGXbu3IlTp07l26tJjDMmd+3ahT59+qBXr14IDw/H+/fvAXzcJGPWrFmifiH7rcRyoztt2jQ0adJEXqCLioqCt7c3+vbtC0dHR8ybNw+lS5fG1KlThQ2qJIGBgbCwsEC7du0AAOPGjcPq1atRuXJlbNmyBWXLlhU4oXLUqVMHsbGxalWge/nypfwFubGxMV6+fAkAaNiwIQYPHixkNKX75Zdf8PLlS7Ro0QLnzp3Dtm3b5L/LuZGA+Kh7AY7yd//+ffkmMURCEX/HdiIB2dnZYfv27XmOb9u2Dfb29gIkImVq3Lgxjh8/DuDjsrCRI0eif//+6NGjB5o3by5wOuX59ddf0adPH8THx8PQ0BAmJiYKf8RoxowZWLlyJdasWaOwNKZBgwZqvzQml1hudK9fv67w+N26dSvq1KmDNWvWYNSoUViyZEm+v+fFYtasWdDT0wPwcTbh8uXLMXfuXFhYWIiuTcOnhg8fjtGjRyMgIABXr15FZGSkwh8xKl++vHxmf6VKleT/rvfv3w9TU1MBk6nGuHHj0KtXL9SsWRNz5szB0aNHWZwjtbRq1SqUKFFC6BhEaokz6IiUyM/PD927d8eZM2fkN3nnz59HcHCwqF/Qqatly5YhIyMDADBx4kRoaWkhNDQUXbt2xaRJkwROpzwbN27E7t270bZtW6GjqMydO3fy3cXRxMQEKSkpqg9ESvPq1SuFFyohISFo06aN/ONatWohMTFRiGgqkZiYKJ9FFhQUhK5du2LAgAFo0KABmjRpImw4JeratSsAoF+/fvJjEokEMplMtJtEeHl5ISIiAm5ubhg/fjw6dOiAZcuW4cOHD1iwYIHQ8Qpdfjs8WllZQV9fH40bN8alS5dw6dIlANz8RgzMzc0RExMDCwsLmJmZfbElS+7sUbH4p60aevbsKVRUIrXHAh2REnXt2hVhYWFYsGABgoKCAACOjo64dOkSXF1dhQ1Hhe7T3TulUinGjx8vYBrVMTExUbs+JSVLlkRsbCzKlSuncPzcuXNq970QuxIlSiA+Ph7W1tbIzMxEeHi4Qv+it2/f5mkwLiaGhoZITk6GjY0Njh07hlGjRgEAdHV18e7dO4HTKY/YesR+i09nRLZo0QLR0dG4evUq7OzsRLkr98KFC/M9rqGhgfPnz+P8+fMAPhZmWaAr+hYuXAgjIyMAwKJFi4QNo2Lq3qqBqChhgY5IyWrUqIHNmzcLHYNUJDs7G0FBQbh9+zYAoEqVKnB3d4eGhobAyZRn6tSp8PPzw/r16+VL4cSuf//+GDlyJNavXw+JRILHjx/jwoULGDNmDCZPnix0PCpEbdu2xfjx4/HHH38gKCgI+vr6Cg3jIyMjUaFCBQETKtd//vMf/PLLL3B1dUVMTIx8pmzuhjhiJdbeev9E2bJlRf19UMcirDrz9PQEAGRlZUEikaBVq1Zqs4zz+vXrmD59uvzjT1s1AIC1tTV8fX1ZoCP6AbBAR6QEUqn0q7uZSiQSZGVlqSgRqUJsbCzatWuHhw8fomLFigCA2bNnw9raGgcPHhTti/hu3bphy5YtsLS0RLly5fLMJhJjT7bx48cjJycHzZs3R3p6Oho3bgwdHR2MGTMGw4cPFzoeFaLp06ejS5cucHNzg6GhIQIDA6GtrS0/v379erRs2VLAhMq1fPlyTJo0CYmJidi1axeKFSsGALh69Sp69OghcDrlu3XrFhISEpCZmalw3N3dXaBEyjNixAjY2dnlmS22bNkyxMbGqt2sIxInTU1NDBo0SP5GqjpQ91YNREWJRCaTyYQOQSQ2e/fuLfDchQsXsGTJEuTk5Mj7lZE4tG3bFjKZDJs3b5Yvd01OTkbv3r0hlUpx8OBBgRMqR7du3XDq1Cn897//RYkSJfIUp8W8W1pmZiZiY2ORmpqKypUrw9DQUOhIPwwjIyNERESIZsnv69evYWhomGc27MuXL2FoaKhQtKOi7969e+jcuTOioqLkvecAyH+/ibEHnZWVFfbt24caNWooHA8PD4e7uzsePnwoUDLl69q1K2rXrg0fHx+F43PnzsXly5exY8cOgZKRMjRp0gS//vorOnXqJHQUlShbtiw2btyIxo0bIzMzE6ampti/f798A6SoqCi4ubmJrvfeP/X333+jY8eOMDAwEDoKqTEW6IhU5M6dOxg/fjz279+PXr16Ydq0aaJeOqKODAwMcPHiRTg5OSkcj4iIQIMGDZCamipQMuUyMDDA0aNH0bBhQ6Gj0A9EzDe6uYWKMmXKCJxE+Y4cOQJDQ0P543v58uVYs2YNKleujOXLl8PMzEzghMrRoUMHaGhoYO3atbC1tcWlS5eQnJyM0aNH488//1RY5iwWurq6uHHjhnxTkFyxsbGoWrWqqN9ULF68OE6ePJnn+TsqKgotWrRAUlKSQMlIGbZv347ff/8dv/32G2rUqJHneUpsPRcHDx6MiIgIeauGwMBAPH78WP7G0ubNm7Fo0SJcvnxZ4KSF659ujkH0I5AKHYBI7B4/foz+/fvDyckJWVlZuH79OgIDA1mcEyEdHR28ffs2z/HU1FRRz66xtraGsbGx0DGUrkuXLnjz5o38/7/0x8PDA3/88Qdev34tcOrCc+HCBRw4cEDh2IYNG2BrawtLS0sMGDAA79+/l5/r2bOnqIpzOTk5mDZtGkxMTOS9uUxNTTF9+nTk5OQIHU9pxo4dK/93HxUVhdGjR6Nt27aIj4+XbxghRhcuXMC0adNgYWEBqVQKqVSKhg0bYvbs2aLdMMDOzg5HjhzJc/zw4cOimQlbkIKep7W0tOT//kk8fv75Z8THx2PEiBFo0KABqlWrBldXV/l/xWb69OnQ1NSEm5sb1qxZgzVr1qhFq4Zp06bh5s2b8o9zN8do0aKFfNLE7NmzBUxIlBd70BEpyevXrzFr1iwsXboU1apVQ3BwsCjfcaf/ad++PQYMGIB169ahdu3aAICwsDAMGjRIlP2Kcs2fPx/jxo3DypUrRd003sTERL68zcTE5IvXvn//HitXrsT58+exb98+VcRTOnXfBW7ixIlYt24d5syZgwYNGgD4uGvv1KlTkZGRgZkzZwqcUDni4+NRuXJlAMCuXbvQvn17zJo1C+Hh4fINI8QoOztbvuOjhYUFHj9+jIoVK6Js2bK4c+eOwOmUY9SoURg2bBieP3+OZs2aAQCCg4Mxf/580fefc3JywrZt2zBlyhSF41u3bpX/+yfxULcNQiwsLHDmzJkCWzXs2LFDlC06uDkGFUkyIip0f/zxh8zc3FxWuXJlWVBQkNBxSEVevXolc3d3l0kkEpm2trZMW1tbJpVKZZ06dZKlpKQIHU9pTE1N5WM1NDSUmZmZKfxRVzdv3pTp6+sLHaPQlCxZUnb58mX5xxMmTJA1aNBA/vH27dtljo6OQkRTiVKlSsn27t2b53hQUJCsdOnSAiRSDTMzM9nNmzdlMplM1qBBA9mqVatkMplMFh8fL9PT0xMymlI1bNhQtmfPHplMJpP16NFD1rp1a9m5c+dkHh4esipVqggbTon++usvmZWVlUwikcgkEonM1tZWFhgYKHQspdu3b59MU1NT5uHhIQsICJAFBATI+vTpI9PU1JT/OyASk8TERFliYqLQMZRKR0dHlpCQIP+4QYMGshkzZsg/jo+PlxkaGgoRjahA7EFHpARSqRR6enpo0aJFnnepPrV7924VpiJVuXv3LqKjowEAjo6Oefr5iE1gYOAXz3t6eqooyY8lOzsbN27cgIuLi9BRCoWuri7u3r0La2trAEDDhg3Rpk0bTJw4EQBw//59ODk55bvMWwx0dXURGRkJBwcHheN37txBtWrV8O7dO4GSKZe7uzsyMzPRoEEDTJ8+HfHx8bCyssKxY8cwbNgwxMTECB1RKY4ePYq0tDR06dIFsbGxaN++PWJiYlCsWDFs27ZNPsNMrJ4/fw49PT1RzqopyMGDBzFr1ixcv34denp6cHZ2hq+vL9zc3ISORkpw584dLF26VL6bq6OjI4YPH46KFSsKnEx5cnJyMGPGDMyfP1/eF9nIyAijR4/GxIkTIZWKq/sVN8egoohLXImUwMPDI89OlqQ+7O3tYW9vL3QMlVHHAlxaWhrmzJmD4OBgPHv2LE8Psnv37kFDQ0M0xTkAKFGiBOLj42FtbY3MzEyEh4fDz89Pfv7t27fQ0tISMKFyubi4YNmyZViyZInC8WXLlonq5/y5ZcuWYciQIdi5cydWrFgBKysrAB/7krVu3VrgdMrTqlUr+f/b2dkhOjoaL1++hJmZmWif39+9eweZTAZ9fX0UL14cDx48wNq1a1G5cmVR9qf6XLt27dCuXTuhY5AK7Nq1Cz///DNq1qyJevXqAQAuXryIqlWrYuvWrejatavACZVD3Vo1tG3bFuPHj5dvjqGvr6/QbigyMhIVKlQQMCFRXpxBR0T0Hf5Jk/QFCxYoMYmwsrOzERQUJH8nukqVKnB3d//iDNKirEePHggJCUGfPn1QqlSpPC/YR44cKVAy5VHXXeByhYSEoF27drCxsZG/oLtw4QISExNx6NAh9hgVmdevXyM7Oxvm5uYKx1++fAlNTU1RbozTsmVLdOnSBYMGDUJKSgoqVqwIbW1tvHjxAgsWLMDgwYOFjkhUKCpUqIBevXph2rRpCsd9fX2xadMmxMXFCZRMuUqXLo2VK1fm6Yu8d+9eDBkyBI8ePRIomXK8ePECXbp0wblz52BoaIjAwEB07txZfr558+aoW7eu6AqTVLSxQEdE9B2aNm36TddJJBKcPHlSyWmEERsbi7Zt2+LRo0fypSF37tyBtbU1Dh48KMp3J01NTXHw4EH5O9DqgDe6wKNHj/DXX38pLGEfMmQISpcuLXAy1cjIyEBmZqbCMTEWqgCgTZs26NChA4YMGaJwfOXKldi3bx8OHTokUDLlsbCwQEhICKpUqYK1a9di6dKluHbtGnbt2oUpU6bI34ARo+zsbCxcuBDbt29HQkJCnn/nXAInLvr6+oiMjMzTguTu3btwcXFBenq6QMmUS11bNRS0OcbLly9haGiY7w7OREJhgY6IiL5L27ZtIZPJsHnzZvlsk+TkZPTu3RtSqRQHDx4UOGHhs7W1xaFDh+Do6Ch0FJXjja56SUtLg4+PD7Zv347k5OQ857OzswVIpXzm5uY4f/58nsd4dHQ0GjRokO/3oqjT19dHdHQ0bGxs0K1bN1SpUgW+vr5ITExExYoVRVu0AIApU6Zg7dq1GD16NCZNmoSJEyfi/v37CAoKwpQpUzBixAihI1Ihatu2LX766Sd4eXkpHPf398fWrVtx9OhRgZIpV506dVCnTp08rRqGDx+Oy5cv4+LFiwIlU52HDx8CAMqUKSNwEqL8sQcdEZESJCYmAoC8ob6YhYSE4OLFiwpLwYoVK6bQ40Rspk+fjilTpiAwMBD6+vpCx1EpExMT+f9/eqP7+VJAsbl79y727t2L+/fvQyKRoHz58ujUqRNsbW2FjqZU48aNw6lTp7BixQr06dMHy5cvx6NHj7Bq1SrMmTNH6HhK8/79e2RlZeU5/uHDB9HOMrGzs0NQUBA6d+6Mo0eP4rfffgMAPHv2TLQzJXNt3rwZa9asQbt27TB16lT06NEDFSpUgLOzMy5evMgCnci4u7vDx8cHV69eRd26dQF87EG3Y8cO+Pn5Yd++fQrXisXcuXPRrl07nDhxIt9WDWKlbptjUNHGGXRERIUkKysLfn5+WLJkifwGwNDQEMOHD4evr69oG+ibm5vjwIEDqF+/vsLx8+fPo0OHDqJcGuTq6oq4uDjIZDKUK1cuz882PDxcoGTKp443urNnz8aUKVOQk5MDS0tLyGQyPH/+HBoaGpg1axbGjBkjdESlsbGxwYYNG9CkSRMYGxsjPDwcdnZ22LhxI7Zs2SLaF3VNmzZF1apVsXTpUoXjQ4cORWRkJM6ePStQMuXZuXMnevbsiezsbDRv3hzHjh0D8PHf/5kzZ3D48GGBEyqPgYEBbt++DRsbG5QqVQoHDx5E9erVce/ePbi6uuL169dCR6RC9K3PUxKJRHSzhNWxVcPvv/+OdevWwc/PL8/mGP379xd1aw4qejiDjoiokAwfPhy7d+/G3LlzFd6ZnDp1KpKTk7FixQqBEypH+/btMWDAAKxbtw61a9cGAISFhWHQoEGieuf5U506dRI6gmDUbRe4U6dOYdKkSZg8eTJGjhwJMzMzAB+X9C5atAjjx49H7dq10bhxY4GTKsfLly9Rvnx5AB/7zeUW3Bs2bCjqTQNmzJiBFi1aICIiAs2bNwcABAcH4/Lly/LCldj897//RcOGDfHkyROFnYmbN2+u0G/y4cOHKF26tKiK8WXKlMGTJ09gY2ODChUq4NixY6hevTouX74MHR0doeNRIft853V1YmVlJbrn6a8JDAzE2rVrFe5JnZ2dYWVlhSFDhqjd94N+bJxBR0RUSExMTLB161a0adNG4fihQ4fQo0cP0b4Dn5KSAk9PT+zfv18+kywrKwvu7u4ICAhQWBJJRZ+67QLXvXt3mJqaYtWqVfmeHzBgAN6+fYstW7aoOJlqODs7Y+nSpXBzc0OLFi1QrVo1/Pnnn1iyZAnmzp0rX+YsRtevX8e8efNw/fp16OnpwdnZGb///jvs7e2FjiYoY2NjXL9+XV64FYPx48fD2NgYEyZMwLZt29C7d2+UK1cOCQkJ+O2330S9nFvdfPjwAa1bt8bKlSvV7rGsrq0a1HVzDCqaWKAjIioklpaWCAkJydNU/Pbt22jcuDGeP38uUDLViI2Nle/y5+jomGd3NBIHdbvRtbW1xcaNG9GwYcN8z589exYeHh6Ij49XcTLVWLhwITQ0NDBixAicOHECHTp0gEwmw4cPH7BgwQKMHDlS6IikYkZGRoiIiBBVge5zFy9eRGhoKOzt7dGhQweh41AhK168uPznqy7UuVUDN8egooRLXImICsmwYcMwffp0+Pv7y5fEvH//HjNnzsSwYcMETqd8dnZ2sLOzQ3Z2NqKiovDq1Sv5ckAxMDc3R0xMDCwsLGBmZgaJRFLgtWLsu5fLxcUFy5Yty3Oju2zZMoVlcWKRlJSEcuXKFXje1tYWT58+VV0gFcnJycG8efOwb98+ZGZm4vHjx/D19UV0dDSuXr0KOzs7ODs7Cx2z0GVlZSE7O1thWWNSUhJWrlyJtLQ0uLu7F1ispaIrOTkZxYoVAwB5w/x3796hZs2aAicjZejdu7e8VYM6UPdWDeq6OQYVTZxBR0RUSDp37ozg4GDo6OjICxURERHIzMyU9zDKtXv3biEiKsWvv/4KJycneHt7Izs7G25ubggNDYW+vj4OHDiAJk2aCB2xUAQGBuLnn3+Gjo4OAgMDv3itp6enilKpXkhICNq1awcbG5t8b3QbNWokcMLCJZVK8fTpU1haWuZ7PikpCaVLlxZdI/Hp06dj6tSpaNGiBfT09HD06FH06NED69evFzqaUnl5eUFbW1u+pPnt27eoUqUKMjIyUKpUKdy6dQt79+5F27ZtBU4qHDHNoIuKikKHDh2QmJgIe3t7bN26Fa1bt0ZaWhqkUinS0tKwc+dOte47KkbDhw/Hhg0bYG9vjxo1asDAwEDh/IIFCwRKphzq3qoBUM/NMahoYoGOiKiQeHl5ffO1/v7+SkyiWmXKlEFQUBBq1qyJoKAgDBkyBKdPn8bGjRtx8uRJnD9/XuiIgpkzZw4GDRoEU1NToaMUKnW60ZVKpZgxYwYMDQ3zPf/27VtMmTJFdAU6e3t7jBkzBgMHDgQAnDhxAu3atcO7d+9EtTnA5xwcHLBs2TK0bNkSALB8+XLMmjULt27dgomJCXx8fHDp0iWcOnVK4KTCEVOBrk2bNtDU1MT48eOxceNGHDhwAK1atcKaNWsAfCzkXL16lUvgRKZp06YFnpNIJDh58qQK0yifurdqICpKWKAjIqLvoquri9jYWJQpUwYDBgyAvr4+Fi1ahPj4eLi4uODNmzdCRxSMGJupq5ty5cp9cTlzLrG9sNHR0UFsbCysra3lxz59rIuVgYEBbty4IW+a3qVLF5QpU0a+pPvWrVto0qQJnj17JmRMQYnp95qFhQVOnjwJZ2dnpKamwtjYGJcvX0aNGjUAANHR0ahbty5SUlKEDUr0HfT19RETE1Pg7+6HDx/C3t5edD1kc6nr5hhUNLEHHRHRdyqoH5mJiQkcHBwwZswY/Oc//xEgmWqUKFECt27dQqlSpXDkyBGsWLECAJCeng4NDQ2B0wlLjO+BqduN7v3794WOIIisrCzo6uoqHNPS0sKHDx8ESqQaurq6Ci9SL168iHnz5imcT01NFSLaD0NMv9devnyJkiVLAgAMDQ1hYGCg0DvVzMwMb9++FSoeKVlsbCzi4uLQuHFj6OnpQSaTfdMbMkVNRkYGtLW1CzyvpaWFzMxMFSZSnYI2x/Dx8RH95hhUNLFAR0T0nRYtWpTv8ZSUFFy9ehXt27fHzp07RbsTnJeXF7p164ZSpUpBIpGgRYsWAICwsDBUqlRJ4HRUmNT1RjcnJwcBAQHYvXu3QmGya9eu6NOnjyhf0MlkMvTt21dhs4SMjAwMGjRIoV+TmPppAkC1atWwceNGzJ49G2fPnkVSUhKaNWsmPx8XFyfKpdzAx9YL3bt3h76+/hevu3Xrlqi+B58/fsX4eCZFycnJ6NatG06dOgWJRIK7d++ifPny8Pb2hpmZGebPny90xEK3du3aL7ZqECN13xyDiiYucSUiUrIFCxZg586dCA0NFTqK0uzcuROJiYn46aef5EsoAgMDYWpqio4dOwqcTjhi6tV06tQptGjRosAb3VmzZuHkyZOiu9GVyWRo3749Dh8+DBcXF1SqVAkymQy3b99GVFQU3N3dERQUJHTMQvetPTXF1E8T+LgJSps2bVCqVCk8efIEPXr0wLp16+TnhwwZgrS0tK9uFFMUlShRAu/evcNPP/0Eb29v1K9fX+hISieVStGmTRt5IXr//v1o1qyZvAj9/v17HDlyRHQ9JtWdh4cHnj17hrVr18LR0VH+PH306FGMGjUKN2/eFDpioVLXVg3cHIOKIhboiIiULCYmBnXr1sXLly+FjkIqJqYCnbre6Pr7+2PkyJHYu3dvnsbiJ0+eRKdOnbBs2TJ4eHgIlJAK2+3bt3Hs2DGULFkSP/30k8KmGKtXr0bt2rVRrVo14QIqSVZWFvbv34+AgAAcPnwY5cuXh5eXFzw9PeXLQMVGXQvR6q5kyZI4evQoXFxcFJ6n7927J+9HSEUfN8egoogFOiIiJYuKisJ//vMfPH36VOgoShMcHIzg4GA8e/YMOTk5CufWr18vUCrhialAp643ui1btkSzZs0wfvz4fM/PmjULISEhOHr0qIqT0Y+gXbt2WLt2LUqVKiV0lEKVlJSETZs2ITAwENHR0WjdujW8vb3RoUMHUe/iS+rByMgI4eHhsLe3V3ievnLlClq1aoXk5GShIxY6dWzVoO6bY1DRxGdYIiIlW7dunShnW+Ty8/NDy5YtERwcjBcvXuDVq1cKf9RJenq6wlLmRo0aQU9PT8BEhScpKQnlypUr8Lytra0oi9CRkZFo3bp1gefbtGmDiIgIFSaiH8mZM2dE+eKuRIkSaNiwIerVqwepVIqoqCh4enqiQoUKOH36tNDxiL5Lo0aNsGHDBvnHEokEOTk5mDt3bp6Z0mIgk8nQoUMH/PLLL3j06BGcnJxQpUoV3L9/H3379kXnzp2FjqgU6rw5BhVd3CSCiOg7jRo1Kt/jr1+/Rnh4OGJiYnDmzBkVp1KdlStXIiAgAH369BE6iuDu3r2LRo0ayfsVHTp0SOBEhUddb3RfvnyJEiVKFHi+RIkSaleIJvFKSkrCxo0b4e/vj3v37qFTp044cOAAWrRogbS0NEybNg2enp548OCB0FGJ/rW5c+eiefPmuHLlCjIzMzFu3DjcvHkTL1++xPnz54WOV+gCAgJw9uxZBAcHF9iqYcOGDaJs1aCOm2NQ0cYlrkRE36mgd1uNjY1RsWJFDB48GLa2tipOpTrFihXDpUuXUKFCBaGjCC4iIgLVq1cXZUNxqVSKGTNmfPFGd8qUKaIbu4aGBp4+fYrixYvnez4pKQmlS5cW3bjp24hpGXuHDh1w9OhRODg44JdffoGHhwfMzc0Vrnn27BlKliyZp5UBUVHz+vVrLFu2DBEREUhNTUX16tUxdOhQ0S1XB9S3VYO6bo5BRRsLdERE9F18fHxgaGiIyZMnCx1FcGIu0Knrje7nuzx+jrs8qjcxFei8vb3xyy+/oF69egVeI5PJkJCQgLJly6owGRF9j5IlS+LIkSMFtlu5du0a2rRpI8o2FURFDZe4EhHRd8nIyMDq1atx4sQJODs7Q0tLS+H8ggULBEpGhen+/ftCRxCEp6fnV68R47IgUj9ubm6oXr16nuOZmZnYunUrPDw8IJFIWJyjIi8yMjLf4xKJBLq6urCxsSnwTZmiSJ1bNajj5hhUtHEGHRERfZcvNVSWSCQ4efKkCtMo1759+754Pj4+HqNGjRLtbCre6BIpEtMMOg0NDTx58gSWlpYKx5OTk2FpaSna32ukfqRSqfz5Kvel8KfPX1paWujevTtWrVoFXV1dQTIWJnVt1SCTydC+fXscPnwYLi4uqFSpEmQyGW7fvo2oqCi4u7sjKChI6JhECjiDjoiIvsupU6eEjqAynTp1+uo1Yi1S5e4Cl3uj6+TkJL/R7du3L3bv3s0bXRKNM2fOoH79+tDUVLxVzsrKQmhoKBo3bgwAmDBhQp4+bUWVTCbL9/fXw4cPYWJiIkAiIuXYs2cPfHx8MHbsWNSuXRsAcOnSJcyfPx++vr7IysrC+PHjMWnSJPz5558Cp/1+MpkMffv2/WKrBjFS580xqOjiDDoiIiL6Kn9/f4wcORJ79+4t8EZ32bJlvNElUVCn2WSurq6QSCSIiIhAlSpVFIqS2dnZiI+PR+vWrbF9+3YBUxIVntq1a2P69Olo1aqVwvGjR49i8uTJuHTpEoKCgjB69GjExcUJlLLweHl5fdN1/v7+Sk6iWuq6OQYVbZxBR0RE3+3KlSvYvn07EhISkJmZqXBu9+7dAqWiwrRlyxZMmDAh3yXNuTfAmzdvZoGORKGg2WTJyckwMDAQIJHy5M4Mvn79Olq1aqWwU7O2tjbKlSuHrl27CpSOqPBFRUXl20uxbNmyiIqKAgBUq1YNT548UXU0pRBb4e1bRUZGYu7cuQWeb9OmDZYsWaLCRERfxwIdERF9l9zm4a1atcKxY8fQsmVLxMTEICkpCZ07dxY6nlLs2LEDW7ZsQUxMDLS1teHg4AAvL68878aLCW90SR106dIFwMel6p8vCcvOzkZkZCTq168vVDyl8PX1BfBxp+bu3buLoucW0ZdUqlQJc+bMwerVq6GtrQ0A+PDhA+bMmYNKlSoBAB49evTFjRXox6fOm2NQ0cUCHRERfZdZs2Zh4cKFGDp0KIyMjLB48WLY2tpi4MCBKFWqlNDxClVOTg569OiBHTt2wMHBQX4jf+3aNezYsQMDBgzAihUrkJycjDNnzoiqQMkbXVIHub3WZDIZjIyMoKenJz+nra2NunXron///kLFU6pv2bGYSAyWL18Od3d3lClTBs7OzgA+zqrLzs7GgQMHAAD37t3DkCFDhIxJ3yk7OztPH9FPaWhoICsrS4WJiL6OBToiIvoucXFxaNeuHYCPL2DT0tIgkUjw22+/oVmzZvDz8xM4YeFZvHgxTpw4gX379qF9+/YK5/bt2wcvLy9UqFABAQEBolvqyRtdUgf+/v7yXR2XLl2qsNxTjMzNzRETEwMLCwuYmZl9cZObly9fqjAZkfLUr18f8fHx2Lx5M2JiYgAAP/30E3r27AkjIyMAQJ8+fYSMSIVAXTfHoKKNBToiIvouZmZmePv2LQDAysoKN27cgJOTE1JSUpCeni5wusLl7++PefPm5SnOAYC7uzvmzp2LAQMGoGXLlvj1119VH1CJeKNL6kImk2Hz5s2YMGEC7O3thY6jVAsXLpQXJBYuXCjaXaiJPmdkZIRBgwYJHYOU6FtmBYvtzVQq+riLKxERfZeePXuiZs2aGDVqFKZPn46lS5eiY8eOOH78OFxdXbFnzx6hIxYaPT093LlzBzY2Nvmef/DgAcqXL493797J+9qIhbruAkfqqUqVKli3bh3q1q0rdBQiUoK7d+/i1KlTePbsGXJychTOTZkyRaBURKTuWKAjIqLv8vLlS2RkZKB06dLIycnB3LlzERoaCnt7e4wZM0ZUfejMzc1x+vRpec+az0VFRaFx48bsxUZUxO3fvx9z587FihUrULVqVaHjKM2bN2+++VpjY2MlJiFSnTVr1mDw4MGwsLBAyZIlFWaOSiQShIeHC5iOiNQZC3RERFToMjIysHz5csybNw9Pnz4VOk6hadeuHWxsbLBixYp8zw8aNAgJCQk4dOiQipMRUWEyMzNDeno6srKyoK2trbBZBCCefmxSqfSry1plMhkkEgmys7NVlIpIucqWLYshQ4bAx8dH6ChERArYg46IiP6V9+/fY+rUqTh+/Di0tbUxbtw4dOrUCf7+/pg0aRI0NDTw22+/CR2zUE2cOBFNmjRBcnIyxowZg0qVKkEmk+H27duYP38+9u7di1OnTgkdk4i+06JFi4SOoBL8fUXq6NWrV/jpp5+EjkFElAdn0BER0b/i4+ODVatWoUWLFggNDcXz58/h5eWFixcvYsKECfjpp5+goaEhdMxCt2fPHgwYMEBhBo1MJoO5uTlWrVqFrl27CpiOiIiIvsTb2xu1atXiJhFE9MPhDDoiIvpXduzYgQ0bNsDd3R03btyAs7MzsrKyEBERIeqdADt37oxWrVrh6NGjuHv3LgDAwcEBrVq1yrMMjoiKruzsbAQFBeH27dsAPm4c4e7uLqo3HiIjI1G1alVIpVJERkZ+8dqCem8SFTV2dnaYPHkyLl68CCcnJ2hpaSmcHzFihEDJiEjdcQYdERH9K9ra2oiPj4eVlRWAjzucXrp0CU5OTgInU54LFy4gOTkZ7du3lx8LDAzE1KlTkZaWhk6dOmHp0qXQ0dERMCURfa/Y2Fi0bdsWjx49QsWKFQEAd+7cgbW1NQ4ePIgKFSoInLBwSKVSPH36FJaWlvJ+dPm9NGAPOhITW1vbAs9JJBLcu3dPhWmIiP6HBToiIvpXNDQ08PTpUxQvXhwAYGRkhMjIyC/e+BZ1bdq0QZMmTeSNpaOiolCjRg14enrC0dER8+bNw8CBAzF16lRhgxLRd2nbti1kMhk2b94Mc3NzAEBycjJ69+4NqVSKgwcPCpywcDx48AA2NjaQSCR48ODBF68tW7asilIRERGpJxboiIjoX5FKpWjTpo18ttj+/fvRrFkzGBgYKFy3e/duIeIpRalSpbB//37UrFkTwMdNI0JCQnDu3DkAH5f9+vr64tatW0LGJKLvZGBgIF/+9qmIiAg0aNAAqampAiUjIiIisWIPOiIi+lc8PT0VPu7du7dASVTn1atXKFGihPzjkJAQtGnTRv5xrVq1kJiYKEQ0IipEOjo6ePv2bZ7jqamp0NbWFiCRaty5cwdLly6V991zdHTE8OHD5ct8iYqqUaNGYfr06TAwMMCoUaO+eO2CBQtUlIqISBELdERE9K/4+/sLHUHlSpQogfj4eFhbWyMzMxPh4eHw8/OTn3/79m2eZtNEVPS0b98eAwYMwLp161C7dm0AQFhYGAYNGgR3d3eB0ynHrl278PPPP6NmzZqoV68eAODixYuoWrUqtm7dyh2qqUi7du0aoqOj4erqimvXrhV4nZg3uSKiHx+XuBIREX2jwYMHIyIiAn/88QeCgoIQGBiIx48fy2fUbN68GYsWLcLly5cFTkpE3yMlJQV9+/bF/v37oan58f3srKwsuLu7IyAgACYmJgInLHwVKlRAr169MG3aNIXjvr6+2LRpE+Li4gRKRlQ4NDQ08OTJE1haWgIAunfvjiVLlijMjCciEhILdERERN/oxYsX6NKlC86dOwdDQ0MEBgaic+fO8vPNmzdH3bp1MXPmTAFTEtG/lZOTg3nz5mHfvn3IzMyEjY0NPD09IZFI4OjoCDs7O6EjKo2+vj4iIyPzjPHu3btwcXFBenq6QMmICsenuxYDgLGxMa5fv47y5csLnIyI6CMucSUiIvpGFhYWOHPmDF6/fg1DQ0NoaGgonN+xYwcMDQ0FSkdE32vmzJmYOnUqWrRoAT09PRw6dAgmJiZYv3690NGUrkmTJjh79myeAt25c+fQqFEjgVIRKQ/nqRDRj4YFOiIion+ooOVt5ubmKk5CRIVpw4YN+OuvvzBw4EAAwIkTJ9CuXTusXbsWUqlU4HSFb9++ffL/d3d3h4+PD65evYq6desC+NiDbseOHQq9NomKKolEkqfHHHvOEdGPhEtciYiIiIjwcffW2NhYWFtby4/p6uoiNjYWZcqUETCZcnxr0VEikSA7O1vJaYiUSyqVok2bNtDR0QEA7N+/H82aNYOBgYHCdbt37xYiHhERZ9AREREREQEfN4LQ1dVVOKalpYUPHz4IlEi5cnJyhI5ApDKenp4KH/fu3VugJERE+eMMOiIiIiIi5J1hA+Q/y4YzbIiIiKiwcQYdERERERHyzrAB1GuWTVpaGkJCQpCQkIDMzEyFcyNGjBAoFRERkXrgDDoiIiIiIjV37do1tG3bFunp6UhLS4O5uTlevHgBfX19WFpa4t69e0JHJCIiEjXxbUdFRERERET/yG+//YYOHTrg1atX0NPTw8WLF/HgwQPUqFEDf/75p9DxiIiIRI8z6IiIiIiI1JypqSnCwsJQsWJFmJqa4sKFC3B0dERYWBg8PT0RHR0tdEQiIiJR4ww6IiIiIiI1p6WlBan040sDS0tLJCQkAABMTEyQmJgoZDQiIiK1wE0iiIiIiIjUnKurKy5fvgx7e3u4ublhypQpePHiBTZu3IiqVasKHY+IiEj0uMSViIiIiEjNXblyBW/fvkXTpk3x7NkzeHh4IDQ0FPb29li/fj1cXFyEjkhERCRqLNAREREREakxmUyGxMREWFpaQldXV+g4REREaok96IiIiIiI1JhMJoOdnR17zREREQmIBToiIiIiIjUmlUphb2+P5ORkoaMQERGpLRboiIiIiIjU3Jw5czB27FjcuHFD6ChERERqiT3oiIiIiIjUnJmZGdLT05GVlQVtbW3o6ekpnH/58qVAyYiIiNSDptABiIiIiIhIWIsWLRI6AhERkVrjDDoiIiIiIiIiIiIBsQcdEREREREhLi4OkyZNQo8ePfDs2TMAwOHDh3Hz5k2BkxEREYkfC3RERERERGouJCQETk5OCAsLw+7du5GamgoAiIiIgK+vr8DpiIiIxI8FOiIiIiIiNTd+/HjMmDEDx48fh7a2tvx4s2bNcPHiRQGTERERqQcW6IiIiIiI1FxUVBQ6d+6c57ilpSVevHghQCIiIiL1wgIdEREREZGaMzU1xZMnT/Icv3btGqysrARIREREpF5YoCMiIiIiUnM///wzfHx88PTpU0gkEuTk5OD8+fMYM2YMPDw8hI5HREQkehKZTCYTOgQREREREQknMzMTQ4cORUBAALKzs6GpqYns7Gz07NkTAQEB0NDQEDoiERGRqLFAR0REREREAICEhATcuHEDqampcHV1hb29vdCRiIiI1AILdERERERERERERALSFDoAEREREREJKzs7GwEBAQgODsazZ8+Qk5OjcP7kyZMCJSMiIlIPLNAREREREam5kSNHIiAgAO3atUPVqlUhkUiEjkRERKRWuMSViIiIiEjNWVhYYMOGDWjbtq3QUYiIiNSSVOgAREREREQkLG1tbdjZ2Qkdg4iISG2xQEdEREREpOZGjx6NxYsXg4triIiIhMElrkREREREaq5z5844deoUzM3NUaVKFWhpaSmc3717t0DJiIiI1AM3iSAiIiIiUnOmpqbo3Lmz0DGIiIjUFmfQERERERERERERCYg96IiIiIiIiIiIiATEJa5ERERERGrI1dUVEonkm64NDw9XchoiIiL1xgIdEREREZEa6tSpk9ARiIiI6P+xBx0REREREREREZGA2IOOiIiIiIiIiIhIQFziSkRERESk5qRS6Rf70WVnZ6swDRERkfphgY6IiIiISM3t2bNH4eMPHz7g2rVrCAwMhJ+fn0CpiIiI1Ad70BERERERUb7+/vtvbNu2DXv37hU6ChERkaixQEdERERERPm6d+8enJ2dkZqaKnQUIiIiUeMmEURERERElMe7d++wZMkSWFlZCR2FiIhI9NiDjoiIiIhITd24cQNVq1aFmZmZwiYRMpkMb9++hb6+PjZt2iRgQiIiIvXAJa5ERERERGpKKpWiVq1a8Pb2RkZGBkxMTOTHixcvjjp16sDMzEzglEREROLHAh0RERERkZo6e/Ys/P39sXPnTuTk5KBr167w9vZG48aNhY5GRESkVligIyIiIiJSc2lpadi+fTsCAgJw9uxZ2NnZwdvbG56enihZsqTQ8YiIiESPBToiIiIiIpKLjY2Fv78/Nm7ciKdPn6J169bYt2+f0LGIiIhEjQU6IiIiIiJSkJaWhs2bN+P3339HSkoKsrOzhY5EREQkatzFlYiIiIiIAABnzpzB+vXrsWvXLkilUnTr1g3e3t5CxyIiIhI9zqAjIiIiIlJjjx8/RkBAAAICAhAbG4v69evD29sb3bp1g4GBgdDxiIiI1AJn0BERERERqak2bdrgxIkTsLCwgIeHB/r164eKFSsKHYuIiEjtsEBHRERERKSmtLS0sHPnTrRv3x4aGhpCxyEiIlJbXOJKREREREREREQkIKnQAYiIiIiIiIiIiNQZC3REREREREREREQCYoGOiIiIiIiIiIhIQCzQERERERERERERCYgFOiIiIqIipm/fvujUqZP84yZNmuDXX39VeY7Tp09DIpEgJSVFaV/j87H+G6rISURERPQ9WKAjIiIiKgR9+/aFRCKBRCKBtrY27OzsMG3aNGRlZSn9a+/evRvTp0//pmtVXawqV64cFi1apJKvRURERFRUaQodgIiIiEgsWrduDX9/f7x//x6HDh3C0KFDoaWlhd9//z3PtZmZmdDW1i6Ur2tubl4on4eIiIiIhMEZdERERESFREdHByVLlkTZsmUxePBgtGjRAvv27QPwv6WaM2fOROnSpVGxYkUAQGJiIrp16wZTU1OYm5ujY8eOuH//vvxzZmdnY9SoUTA1NUWxYsUwbtw4yGQyha/7+RLX9+/fw8fHB9bW1tDR0YGdnR3WrVuH+/fvo2nTpgAAMzMzSCQS9O3bFwCQk5OD2bNnw9bWFnp6enBxccHOnTsVvs6hQ4fg4OAAPT09NG3aVCHnv5GdnQ1vb2/516xYsSIWL16c77V+fn4oXrw4jI2NMWjQIGRmZsrPfUv2Tz148AAdOnSAmZkZDAwMUKVKFRw6dOi7xkJERET0PTiDjoiIiEhJ9PT0kJycLP84ODgYxsbGOH78OADgw4cPaNWqFerVq4ezZ89CU1MTM2bMQOvWrREZGQltbW3Mnz8fAQEBWL9+PRwdHTF//nzs2bMHzZo1K/Drenh44MKFC1iyZAlcXFwQHx+PFy9ewNraGrt27ULXrl1x584dGBsbQ09PDwAwe/ZsbNq0CStXroS9vT3OnDmD3r17o3jx4nBzc0NiYiK6dOmCoUOHYsCAAbhy5QpGjx79Xd+fnJwclClTBjt27ECxYsUQGhqKAQMGoFSpUujWrZvC901XVxenT5/G/fv34eXlhWLFimHmzJnflP1zQ4cORWZmJs6cOQMDAwPcunULhoaG3zUWIiIiou/BAh0RERFRIZPJZAgODsbRo0cxfPhw+XEDAwOsXbtWvrR106ZNyMnJwdq1ayGRSAAA/v7+MDU1xenTp9GyZUssWrQIv//+O7p06QIAWLlyJY4ePVrg146JicH27dtx/PhxtGjRAgBQvnx5+fnc5bCWlpYwNTUF8HHG3axZs3DixAnUq1dP/nfOnTuHVatWwc3NDStWrECFChUwf/58AEDFihURFRWFP/74419/n7S0tODn5yf/2NbWFhcuXMD27dsVCnTa2tpYv3499PX1UaVKFUybNg1jx47F9OnT8eHDh69m/1xCQgK6du0KJyenPN8fIiIiIiGwQEdERERUSA4cOABDQ0N8+PABOTk56NmzJ6ZOnSo/7+TkpNB3LiIiArGxsTAyMlL4PBkZGYiLi8Pr16/x5MkT1KlTR35OU1MTNWvWzLPMNdf169ehoaGRb2GqILGxsUhPT8d//vMfheOZmZlwdXUFANy+fVshBwB5Qex7LF++HOvXr0dCQgLevXuHzMxMVKtWTeEaFxcX6OvrK3zd1NRUJCYmIjU19avZPzdixAgMHjwYx44dQ4sWLdC1a1c4Ozt/91iIiIiI/i0W6IiIiIgKSdOmTbFixQpoa2ujdOnS0NRUvNUyMDBQ+Dg1NRU1atTA5s2b83yu4sWL/6sMuUtW/4nU1FQAwMGDB2FlZaVwTkdH51/l+BZbt27FmDFjMH/+fNSrVw9GRkaYN28ewsLCvvlz/Jvsv/zyC1q1aoWDBw/i2LFjmD17NubPn68w25GIiIhIlVigIyIiIiokBgYGsLOz++brq1evjm3btsHS0hLGxsb5XlOqVCmEhYWhcePGAICsrCxcvXoV1atXz/d6Jycn5OTkICQkRL7E9VO5M/iys7PlxypXrgwdHR0kJCQUOPPO0dFRvuFFrosXL359kF9w/vx51K9fH0OGDJEfi4uLy3NdREQE3r17Jy8+Xrx4EYaGhrC2toa5uflXs+fH2toagwYNwqBBg/D7779jzZo1LNARERGRYLiLKxEREZFAevXqBQsLC3Ts2BFnz55FfHw8Tp8+jREjRuDhw4cAgJEjR2LOnDkICgpCdHQ0hgwZgpSUlAI/Z7ly5eDp6Yl+/fohKChI/jm3b98OAChbtiwkEgkOHDiA58+fIzU1FUZGRhgzZgx+++03BAYGIi4uDuHh4Vi6dCkCAwMBAIMGDcLdu3cxduxY3LlzB3///TcCAgK+aZyPHj3C9evXFf68evUK9vb2uHLlCo4ePYqYmBhMnjwZly9fzvP3MzMz4e3tjVu3buHQoUPw9fXFsGHDIJVKvyn753799VccPXoU8fHxCA8Px6lTp+Do6PhNYyEiIiJSBhboiIiIiASir6+PM2fOwMbGBl26dIGjoyO8vb2RkZEhn1E3evRo9OnTB56envJloJ07d/7i512xYgX++9//YsiQIahUqRL69++PtLQ0AICVlRX8/Pwwfvx4lChRAsOGDQMATJ8+HZMnT8bs2bPh6OiI1q1b4+DBg7C1tQUA2NjYYNeuXQgKCoKLiwtWrlyJWbNmfdM4//zzT7i6uir8OXjwIAYOHIguXbqge/fuqFOnDpKTkxVm0+Vq3rw57O3t0bhxY3Tv3h3u7u4Kvf2+lv1z2dnZGDp0qPxaBwcH/PXXX980FiIiIiJlkMgK6jBMRERERERERERESscZdERERERERERERAJigY6IiIiIiIiIiEhALNAREREREREREREJiAU6IiIiIiIiIiIiAbFAR0REREREREREJCAW6IiIiIiIiIiIiATEAh0REREREREREZGAWKAjIiIiIiIiIiISEAt0REREREREREREAmKBjoiIiIiIiIiISEAs0BEREREREREREQno/wD9x+afyNKKygAAAABJRU5ErkJggg=="},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 0 Axes>"},"metadata":{}}]}]}